Gate-All-Around Nanopore Osmotic Power Generators

Nanofluidic channels in a membrane represent a promising avenue for harnessing blue energy from salinity gradients, relying on permselectivity as a pivotal characteristic crucial for inducing electricity through diffusive ion transport. Surface charge emerges as a central player in the osmotic energy conversion process, emphasizing the critical significance of a judicious selection of membrane materials to achieve optimal ion permeability and selectivity within specific channel dimensions. Alternatively, here we report a field-effect approach for in situ manipulation of the ion selectivity in a nanopore. Application of voltage to a surround-gate electrode allows precise adjustment of the surface charge density at the pore wall. Leveraging the gating control, we demonstrate permselectivity turnover to enhanced cation selective transport in multipore membranes, resulting in a 6-fold increase in the energy conversion efficiency with a power density of 15 W/m2 under a salinity gradient. These findings not only advance our fundamental understanding of ion transport in nanochannels but also provide a scalable and efficient strategy for nanoporous membrane osmotic power generation.

Geometrically Scalable Iontronic Memristors: Employing Bipolar Polyelectrolyte Gels for Neuromorphic Systems

Iontronics that are capable of mimicking the functionality of biological systems within an artificial fluidic network have long been pursued for biomedical applications and ion-based intelligence systems. Here, we report on facile and robust realization of iontronic bipolar memristors featuring a three-layer polyelectrolyte gel structure. Significant memristive hysteresis of ion currents was successfully accomplished, and the memory time proved geometrically scalable from 200 to 4000 s. These characteristics were enabled by the ion concentration polarization-induced rectification ratio within the polyelectrolyte gels. The memristors exhibited memory dynamics akin to those observed in unipolar devices, while the bipolar structure notably enabled prolonged memory time and enhanced the ion conductance switching ratio with mesoscale (10-1000 μm) geometry precision. These properties endow the devices with the capability of effective neuromorphic processing with pulse-based input voltage signals. Owing to their simple fabrication process and superior memristive performance, the presented iontronic bipolar memristors are versatile and can be easily integrated into small-scale iontronic circuits, thereby facilitating advanced neuromorphic computing functionalities.

Ion-Fluid Transport-Control Feedback along Nanopore Networks

Biological signaling correlates with the interrelation between ion and nanofluidic transportation pathways. However, artificial embodies with reconfigurable ion-fluid transport interaction aspects remain largely elusive. Herein, we unveiled an intimate interplay between nanopore-driven advancing flow and ion carriage for the spontaneous imbibition of aqueous solutions at the nanoporous thin film level. Ionic factors dominate transport phenomena processing and integration (ions influence fluid motion, which in turn governs the self-regulated ion traveling). We show an ion-induced translation effect that finely converts a chemical input, the nature of ions, into a related fluidic output: modulation of the extent of imbibition. We further find complex imbibition dynamics induced by the ion type and population. We peculiarly pinpoint a stop-and-go effective transport process with a programmable delay time triggered by selective guest-host interactions. The ion-fluid transport interplay is captured by a simple model that considers the counterbalance between the capillary infiltration and solution concentration, owing to water loss at the nanoporous film-air interface. Our results demonstrate that nanopore networks present fresh scenarios for understanding and controlling autonomous macroscopic liquid locomotion and offer a distinctive working principle for smart ion operation.

Tuning Interfacial Water Friction through Moiré Twist

Foundations of nanofluidics can enable advances in diverse applications such as water desalination, energy harvesting, and biological analysis. Dynamically manipulating nanofluidic properties, such as diffusion and friction, is an area of great scientific interest. Twisted bilayer graphene, particularly at the magic angle, has garnered attention for its unconventional superconductivity and correlated insulator behavior due to strong electronic correlations. The impact of the electronic properties of moiré patterns in twisted bilayer graphene on structural and dynamic properties of water remains largely unexplored. Computational challenges, stemming from simulating large unit cells using density functional theory, have hindered progress. This study addresses this gap by investigating water behavior on twisted bilayer graphene, employing a deep neural network potential (DP) model trained with a data set from ab initio molecular dynamics simulations. It is found that as the twisted angle approaches the magic angle, interfacial water friction increases, leading to a reduced water diffusion. Notably, the analysis shows that at smaller twisted angles with larger moiré patterns, water is more likely to reside in AA stacking regions than AB (or BA) stacking regions, a distinction that diminishes with smaller moiré patterns. This study illustrates the potential for leveraging the distinctive properties of moiré systems to effectively control and optimize interfacial fluid behavior.

Artificial Funnel Nanochannel Device Emulates Synaptic Behavior

Creating artificial synapses that can interact with biological neural systems is critical for developing advanced intelligent systems. However, there are still many difficulties, including device morphology and fluid selection. Based on Micro-Electro-Mechanical System technologies, we utilized two immiscible electrolytes to form a liquid/liquid interface at the tip of a funnel nanochannel, effectively enabling a wafer-level fabrication, interactions between multiple information carriers, and electron-to-chemical signal transitions. The distinctive ionic transport properties successfully achieved a hysteresis in ionic transport, resulting in adjustable multistage conductance gradient and synaptic functions. Notably, the device is similar to biological systems in terms of structure and signal carriers, especially for the low operating voltage (200 mV), which matches the biological neural potential (∼110 mV). This work lays the foundation for realizing the function of iontronics neuromorphic computing at ultralow operating voltages and in-memory computing, which can break the limits of information barriers for brain-machine interfaces.

Threshold current density for diffusion-controlled stability of electrolytic surface nanobubbles

Understanding the stability mechanism of surface micro/nanobubbles adhered to gas-evolving electrodes is essential for improving the efficiency of water electrolysis, which is known to be hindered by the bubble coverage on electrodes. Using molecular simulations, the diffusion-controlled evolution of single electrolytic nanobubbles on wettability-patterned nanoelectrodes is investigated. These nanoelectrodes feature hydrophobic islands as preferential nucleation sites and allow the growth of nanobubbles in the pinning mode. In these simulations, a threshold current density distinguishing stable nanobubbles from unstable nanobubbles is found. When the current density remains below the threshold value, nucleated nanobubbles grow to their equilibrium states, maintaining their nanoscopic size. However, for the current density above the threshold value, nanobubbles undergo unlimited growth and can eventually detach due to buoyancy. Increasing the pinning length of nanobubbles increases the degree of nanobubble instability. By connecting the current density with the local gas oversaturation, an extension of the stability theory for surface nanobubbles [Lohse and Zhang, Phys. Rev. E 91, 031003(R) (2015)] accurately predicts the nanobubble behavior found in molecular simulations, including equilibrium contact angles and the threshold current density. For larger systems that are not accessible to molecular simulations, continuum numerical simulations with the finite difference method combined with the immersed boundary method are performed, again demonstrating good agreement between numerics and theories.

Giant Blue Energy Harvesting in Two-Dimensional Polymer Membranes with Spatially Aligned Charges

Blue energy between seawater and river water is attracting increasing interest, as one of the sustainable and renewable energy resources that can be harvested from water. Within the reverse electrodialysis applied in blue energy conversion, novel membranes with nanoscale confinement that function as selective ion transport mediums are currently in high demand for realizing higher power density. The primary challenge lies in constructing well-defined nanochannels that allow for low-energy barrier transport. This work proposes a concept for nanofluidic channels with a simultaneous dual electrostatic effect that can enhance both ion selectivity and flux. To actualize this, this work has synthesized propidium iodide-based two-dimensional polymer (PI-2DP) membranes possessing both skeleton charge and intrinsic space charge, which are spatially aligned along the ion transport pathway. The dual charge design of PI-2DP significantly enhances the electrostatic interaction between the translocating anions and the cationic polymer framework, and a high anion selectivity coefficient (≈0.8) is reached. When mixing standard artificial seawater and river water, this work achieves a considerable power density of 48.4 W m-2, outperforming most state-of-the-art nanofluidic membranes. Moreover, when applied between the Mediterranean Sea and the Elbe River, an output power density of 42.2 W m-2 is achieved by the PI-2DP. This nanofluidic membrane design with dual-layer charges will inspire more innovative development of ion-selective channels for blue energy conversion that will contribute to global energy consumption.

Brain-inspired computing with fluidic iontronic nanochannels

The brain's remarkable and efficient information processing capability is driving research into brain-inspired (neuromorphic) computing paradigms. Artificial aqueous ion channels are emerging as an exciting platform for neuromorphic computing, representing a departure from conventional solid-state devices by directly mimicking the brain's fluidic ion transport. Supported by a quantitative theoretical model, we present easy-to-fabricate tapered microchannels that embed a conducting network of fluidic nanochannels between a colloidal structure. Due to transient salt concentration polarization, our devices are volatile memristors (memory resistors) that are remarkably stable. The voltage-driven net salt flux and accumulation, that underpin the concentration polarization, surprisingly combine into a diffusionlike quadratic dependence of the memory retention time on the channel length, allowing channel design for a specific timescale. We implement our device as a synaptic element for neuromorphic reservoir computing. Individual channels distinguish various time series, that together represent (handwritten) numbers, for subsequent in silico classification with a simple readout function. Our results represent a significant step toward realizing the promise of fluidic ion channels as a platform to emulate the rich aqueous dynamics of the brain.

Boosting Osmotic Energy Harvesting from Organic Solutions by Ultrathin Covalent Organic Framework Membranes

Extracting osmotic energy from waste organic solutions via reverse electrodialysis represents a promising approach to reuse such industrial wastes and helps to mitigate the ever-growing energy needs. Herein, a molecularly thin membrane of covalent organic frameworks is engineered via interfacial polymerization to investigate its ion transport behavior in organic solutions. Interestingly, a significant deviation from linearity between ion conductance and reciprocal viscosity is observed, attributed to the nanoscale confinement effect on intermolecular interactions. This finding suggests a potential strategy to modulate the influence of apprarent viscosity on transmembrane transport. The osmotic energy harvesting of the ultrathin membrane in organic systems was studied, achieving an unprecedented output power density of over 84.5 W m-2 at a 1000-fold salinity gradient with a benign conversion efficiency and excellent stability. These findings provide a meaningful stepping stone for future studies seeking to fully leverage the potentials of organic systems in energy harvesting applications.

An enzymatic continuous-flow reactor based on a pore-size matching nano- and isoporous block copolymer membrane

Continuous-flow biocatalysis utilizing immobilized enzymes emerged as a sustainable route for chemical synthesis. However, inadequate biocatalytic efficiency from current flow reactors, caused by non-productive enzyme immobilization or enzyme-carrier mismatches in size, hampers its widespread application. Here, we demonstrate a general-applicable and robust approach for the fabrication of a high-performance enzymatic continuous-flow reactor via integrating well-designed scalable isoporous block copolymer (BCP) membranes as carriers with an oriented and productive immobilization employing material binding peptides (MBP). Densely packed uniform enzyme-matched nanochannels of well-designed BCP membranes endow the desired nanoconfined environments towards a productive immobilized phytase. Tuning nanochannel properties can further regulate the complex reaction process and fortify the catalytic performance. The synergistic design of enzyme-matched carriers and efficient enzyme immobilization empowers an excellent catalytic performance with >1 month operational stability, superior productivity, and a high space-time yield (1.05 × 105 g L-1 d-1) via a single-pass continuous-flow process. The obtained performance makes the designed nano- and isoporous block copolymer membrane reactor highly attractive for industrial applications.

Rewritable printing of ionic liquid nanofilm utilizing focused ion beam induced film wetting

Manipulating liquid flow over open solid substrate at nanoscale is important for printing, sensing, and energy devices. The predominant methods of liquid maneuvering usually involve complicated surface fabrications, while recent attempts employing external stimuli face difficulties in attaining nanoscale flow control. Here we report a largely unexplored ion beam induced film wetting (IBFW) technology for open surface nanofluidics. Local electrostatic forces, which are generated by the unique charging effect of Helium focused ion beam (HFIB), induce precursor film of ionic liquid and the disjoining pressure propels and stabilizes the nanofilm with desired patterns. The IBFW technique eliminates the complicated surface fabrication procedures to achieve nanoscale flow in a controllable and rewritable manner. By combining with electrochemical deposition, various solid materials with desired patterns can be produced.

Nanofluidic memristor based on the elastic deformation of nanopores with nanoparticle adsorption

The memristor is the building block of neuromorphic computing. We report a new type of nanofluidic memristor based on the principle of elastic strain on polymer nanopores. With nanoparticles absorbed at the wall of a single conical polymer nanopore, we find a pinched hysteresis of the current within a scanning frequency range of 0.01-0.1 Hz, switching to a diode below 0.01 Hz and a resistor above 0.1 Hz. We attribute the current hysteresis to the elastic strain at the tip side of the nanopore, caused by electrical force on the particles adsorbed at the inner wall surface. Our simulation and analytical equations match well with experimental results, with a phase diagram for predicting the system transitions. We demonstrate the plasticity of our nanofluidic memristor to be similar to a biological synapse. Our findings pave a new way for ionic neuromorphic computing using nanofluidic memristors.

Green Alga-Inspired Underwater Vision Based on Light-Driven Active Ion Transport across Janus Dual-Field Heterostructures

Natural organisms have evolved various biological ion channels to make timely responses toward different physical and/or chemical stimuli, giving guidance to construct artificial counterparts and expand the corresponding applications. They have also shown promising potential to overcome disadvantages of traditional electronic devices (e.g., energy-consuming operation and adverse humidity interference). Herein, we constructed a green alga-inspired nanofluidic system based on a Janus dual-field heterogeneous membrane (i.e., J-HM), which can function underwater as an artificial visual platform for light perception through enhanced active ion transport. The J-HM was obtained through sequentially assembled MXene and Cu-HHTP (i.e., a metal-organic framework based on the reaction between 2,3,6,7,10,11-hexahydroxytriphenylene hydrate (HHTP) and Cu2+) building units. Due to the formed temperature gradient and intramembrane electric field caused by the localized thermal excitation and efficient charge separation of J-HM under illumination, thermo-osmotic and photo-driven forces are generated for preferential cation transport from Cu-HHTP to MXene. Furthermore, unidirectional active transport can be enhanced by self-diffusion under a concentration gradient. Then, the corresponding underwater light perceptions at various light illumination conditions are explored, showing nearly a linear correlation with the light intensity. Finally, it is demonstrated that the visual platform can achieve object shape, definition, and distance recognition using a defined pixelated matrix, giving impetus to develop ionic signal transmission based sensing systems.

Single-Crystal Silicon Nanotubes, Hollow Nanocones, and Branched Nanotube Networks

We report a general approach for the synthesis of single-crystal silicon nanotubes, involving epitaxial deposition of silicon shells on germanium nanowire templates followed by removal of the germanium template by selective wet etching. By exploiting advances in the synthesis of germanium nanowires, we were able to rationally tune the nanotube internal diameters (5-80 nm), wall thicknesses (3-12 nm), and taper angles (0-9°) and additionally demonstrated branched silicon nanotube networks. Field effect transistors fabricated from p-type nanotubes exhibited a strong gate effect, and fluid transport experiments demonstrated that small molecules could be electrophoretically driven through the nanotubes. These results demonstrate the suitability of silicon nanotubes for the design of nanoelectrofluidic devices.

Memristive Response and Capacitive Spiking in Aqueous Ion Transport through Two-Dimensional Nanopore Arrays

In living organisms, information is processed in interconnected symphonies of ionic currents spiking through protein ion channels. As a result of dynamic switching of their conductive states, ion channels exhibit a variety of current-voltage nonlinearities and memory effects. Fueled by the promise of computing architectures entirely different from von Neumann, recent attempts to identify and harness similar phenomena in artificial nanofluidic environments focused on demonstrating analogue circuit elements with memory. Here we explore aqueous ionic transport through two-dimensional (2D) membranes featuring arrays of ion-trapping crown-ether-like pores. We demonstrate that for aqueous salts featuring ions with different ion-pore binding affinities, memristive effects emerge through coupling between the time-delayed state of the system and its transport properties. We also demonstrate a nanopore array that behaves as a capacitor with a strain-tunable built-in barrier, yielding behaviors ranging from current spiking to an ohmic response. By focusing on the illustrative underlying mechanisms, we demonstrate that realistically observable memory effects may be achieved in nanofluidic systems featuring crown-porous 2D membranes.

Correlations in Charged Multipore Systems: Implications for Enhancing Selectivity and Permeability in Nanoporous Membranes

Nanoporous membranes have emerged as powerful tools for diverse applications, including gas separation and water desalination. Achieving high permeability for desired molecules alongside exceptional rejection of other species presents a significant design challenge. One potential strategy involves optimizing the chemistry and geometry of isolated nanopores to enhance permeability and selectivity while maximizing their density within a membrane. However, the impact of the pore proximity on membrane performance remains an open question. Through path sampling simulations of model graphitic membranes with multiple subnanometer pores, we reveal that nanoscale proximity between pores detrimentally affects water permeability and salt rejection. Specifically, counterion transport is decelerated, while co-ion transport is accelerated, due to direct interactions among water molecules, salt ions, and the dipoles within neighboring pores. Notably, the observed ionic transport time scales significantly deviate from established theories such as the access resistance model but are well explained using the simple phenomenological model that we develop in this work. We use this model to prescreen and optimize pore arrangements that elicit minimal correlations at a target pore density. These findings deepen our understanding of multipore systems, informing the rational design of nanoporous membranes for enhanced separation processes such as water desalination. They also shed light on the physiology of biological cells that employ ion channel proteins to modulate ion transport and reversal potentials.

Anomalously enhanced ion transport and uptake in functionalized angstrom-scale two-dimensional channels

Emulating angstrom-scale dynamics of the highly selective biological ion channels is a challenging task. Recent work on angstrom-scale artificial channels has expanded our understanding of ion transport and uptake mechanisms under confinement. However, the role of chemical environment in such channels is still not well understood. Here, we report the anomalously enhanced transport and uptake of ions under confined MoS2-based channels that are ~five angstroms in size. The ion uptake preference in the MoS2-based channels can be changed by the selection of surface functional groups and ion uptake sequence due to the interplay between kinetic and thermodynamic factors that depend on whether the ions are mixed or not prior to uptake. Our work offers a holistic picture of ion transport in 2D confinement and highlights ion interplay in this regime.

Ion and Hydrodynamic Translucency in 1D van der Waals Heterostructured Boron-Nitride Single-Walled Carbon Nanotubes

An unresolved challenge in nanofluidics is tuning ion selectivity and hydrodynamic transport in pores, particularly for those with diameters larger than a nanometer. In contrast to conventional strategies that focus on changing surface functionalization or confinement degree by varying the radial dimension of the pores, we explore a unique approach for manipulating ion selectivity and hydrodynamic flow enhancement by externally coating single-walled carbon nanotubes (SWCNTs) with a few layers of hexagonal boron nitride (h-BN). For van der Waals heterostructured BN-SWCNTs, we observed a 9-fold increase in cation selectivity for K+ versus Cl- compared to pristine SWCNTs of the same 2.2 nm diameter, while hydrodynamic slip lengths decreased by more than an order of magnitude. These results suggest that the single-layer graphene inner surface may be translucent to charge-regulation and hydrodynamic-slip effects arising from h-BN on the outside of the SWCNT. Such 1D heterostructures could serve as synthetic platforms with tunable properties for exploring distinct nanofluidic phenomena and their potential applications.

Impact of Single-Walled Carbon Nanotube Functionalization on Ion and Water Molecule Transport at the Nanoscale

Nanofluidics has a very promising future owing to its numerous applications in many domains. It remains, however, very difficult to understand the basic physico-chemical principles that control the behavior of solvents confined in nanometric channels. Here, water and ion transport in carbon nanotubes is investigated using classical force field molecular dynamics simulations. By combining one single walled carbon nanotube (uniformly charged or not) with two perforated graphene sheets, we mimic single nanopore devices similar to experimental ones. The graphitic edges delimit two reservoirs of water and ions in the simulation cell from which a voltage is imposed through the application of an external electric field. By analyzing the evolution of the electrolyte conductivity, the role of the carbon nanotube geometric parameters (radius and chirality) and of the functionalization of the carbon nanotube entrances with OH or COO- groups is investigated for different concentrations of group functions.

Elastocapillarity-driven 2D nano-switches enable zeptoliter-scale liquid encapsulation

Biological nanostructures change their shape and function in response to external stimuli, and significant efforts have been made to design artificial biomimicking devices operating on similar principles. In this work we demonstrate a programmable nanofluidic switch, driven by elastocapillarity, and based on nanochannels built from layered two-dimensional nanomaterials possessing atomically smooth surfaces and exceptional mechanical properties. We explore operational modes of the nanoswitch and develop a theoretical framework to explain the phenomenon. By predicting the switching-reversibility phase diagram-based on material, interfacial and wetting properties, as well as the geometry of the nanofluidic circuit-we rationally design switchable nano-capsules capable of enclosing zeptoliter volumes of liquid, as small as the volumes enclosed in viruses. The nanoswitch will find useful application as an active element in integrated nanofluidic circuitry and could be used to explore nanoconfined chemistry and biochemistry, or be incorporated into shape-programmable materials.

Ultralow Energy Consumption Angstrom-Fluidic Memristor

The emergence of nanofluidic memristors has made a giant leap to mimic the neuromorphic functions of biological neurons. Here, we report neuromorphic signaling using Angstrom-scale funnel-shaped channels with poly-l-lysine (PLL) assembled at nano-openings. We found frequency-dependent current-voltage characteristics under sweeping voltage, which represents a diode in low frequencies, but it showed pinched current hysteresis as frequency increases. The current hysteresis is strongly dependent on pH values but weakly dependent on salt concentration. We attributed the current hysteresis to the entropy barrier of PLL molecules entering and exiting the Angstrom channels, resulting in reversible voltage-gated open-close state transitions. We successfully emulated the synaptic adaptation of Hebbian learning using voltage spikes and obtained a minimum energy consumption of 2-23 fJ in each spike per channel. Our findings pave a new way to mimic neuronal functions by Angstrom channels in low energy consumption.

Hydrophobically gated memristive nanopores for neuromorphic applications

Signal transmission in the brain relies on voltage-gated ion channels, which exhibit the electrical behaviour of memristors, resistors with memory. State-of-the-art technologies currently employ semiconductor-based neuromorphic approaches, which have already demonstrated their efficacy in machine learning systems. However, these approaches still cannot match performance achieved by biological neurons in terms of energy efficiency and size. In this study, we utilise molecular dynamics simulations, continuum models, and electrophysiological experiments to propose and realise a bioinspired hydrophobically gated memristive nanopore. Our findings indicate that hydrophobic gating enables memory through an electrowetting mechanism, and we establish simple design rules accordingly. Through the engineering of a biological nanopore, we successfully replicate the characteristic hysteresis cycles of a memristor and construct a synaptic device capable of learning and forgetting. This advancement offers a promising pathway for the realization of nanoscale, cost- and energy-effective, and adaptable bioinspired memristors.

Nanomechanical Sensing for Mass Flow Control in Nanowire-Based Open Nanofluidic Systems

Open nanofluidic systems, where liquids flow along the outer surface of nanoscale structures, provide otherwise unfeasible capabilities for extremely miniaturized liquid handling applications. A critical step toward fully functional applications is to obtain quantitative mass flow control. We demonstrate the application of nanomechanical sensing for this purpose by integrating voltage-driven liquid flow along nanowire open channels with mass detection based on flexural resonators. This approach is validated by assembling the nanowires with microcantilever resonators, enabling high-precision control of larger flows, and by using the nanowires as resonators themselves, allowing extremely small liquid volume handling. Both implementations are demonstrated by characterizing voltage-driven flow of ionic liquids along the surface of the nanowires. We find a voltage range where mass flow rate follows a nonlinear monotonic increase, establishing a steady flow regime for which we show mass flow control at rates from below 1 ag/s to above 100 fg/s and precise liquid handling down to the zeptoliter scale. The observed behavior of mass flow rate is consistent with a voltage-induced transition from static wetting to dynamic spreading as the mechanism underlying liquid transport along the nanowires.

Label-Free Imaging of Catalytic H2O2 Decomposition on Single Colloidal Pt Nanoparticles Using Nanofluidic Scattering Microscopy

Single-particle catalysis aims at determining factors that dictate the nanoparticle activity and selectivity. Existing methods often use fluorescent model reactions at low reactant concentrations, operate at low pressures, or rely on plasmonic enhancement effects. Hence, methods to measure single-nanoparticle activity under technically relevant conditions and without fluorescence or other enhancement mechanisms are still lacking. Here, we introduce nanofluidic scattering microscopy of catalytic reactions on single colloidal nanoparticles trapped inside nanofluidic channels to fill this gap. By detecting minuscule refractive index changes in a liquid flushed trough a nanochannel, we demonstrate that local H2O2 concentration changes in water can be accurately measured. Applying this principle, we analyze the H2O2 concentration profiles adjacent to single colloidal Pt nanoparticles during catalytic H2O2 decomposition into O2 and H2O and derive the particles' individual turnover frequencies from the growth rate of the O2 gas bubbles formed in their respective nanochannel during reaction.

Investigating the atomic behavior of carbon nanotubes as nanopumps

In this study, we utilized molecular dynamics (MD) simulations to investigate the nano pumping process of Carbon Nanotube (CNT) in an aqueous environment. In this research, an attempt has been made to investigate and analyze the pumping process of fullerene C20 and water molecules through a carbon nanotube that is externally stimulated by two oscillators. It should be noted that this nano pump is completely immersed in an aqueous environment and the inside and outside of the carbon nanotube is filled with water molecules. To simulate the aqueous environment with NaCl impurities and carbon structures, we employed the Universal Force Field and Tersoff interatomic potentials, respectively. The stability of the simulated structures was demonstrated through an equilibrium process, which was a result of the appropriate settings in our MD simulations. To describe the CNT nano pumping process, we analyzed the velocity and translational/rotational components of C20 kinetic energy over time steps. By decreasing the water impurity concentration from 0.50 to 0.075 mol/l, the nano pumping time varied from 10.98 to 10.11 ps, respectively. Additionally, optimization of the atomic wave producing in the nano pumping process led to a further decrease in pumping time to 10.01 ps. Finally, a 2.86% variation in calculated results was observed by changing the water MD simulation model from SPC to TIP4P.