Two-dimensional polymers (2DPs) and their layer-stacked 2D covalent organic frameworks (2D COFs) membranes hold great potential for harvesting sustainable osmotic energy. The nascent research has yet to simultaneously achieve high ionic flux and selectivity, primarily due to inefficient ion transport dynamics. This is directly related to ultrasmall pore size (<3 nm), much smaller than the duple Debye length in the diluted electrolyte (6~20 nm), as well as low charge density (<4.5 mC m-2). Here, we introduce a π-conjugated viologen-based 2DP (V2DP) membrane possessing a large pore size of 4.5 nm, strategically enhancing the overlapping of the electric double layer, coupled with an exceptional positive surface charge density (~6 mC m-2). These characteristics enable the membrane to facilitate high anion flux while maintaining ideal selectivity. Notably, V2DP membranes realize an impressive current density of 5.5×103 A m-2, surpassing  previously nanofluidic membranes. In practical application scenario involving the mixing of artificial seawater and river water, the V2DP membranes exhibit a considerable ion transference number of 0.70 towards Cl-, contributing to an outstanding power density of ~55 W m-2. Theoretical calculations reveal that the large quantity of anion transport sites act as binding sites evenly located in the positively charged N-containing pyridine rings.

Recognition and separation of chiral isomers are of great importance in both industrial and biological applications. However, owing to identical molecular formulas and chemical properties of enantiomers, signal transduction and amplification are still two major challenges in chiral sensing. In this study, we developed an enantioselective device by integrating chiral covalent organic framework nanosheets (CONs) with nanochannels for sensitive identification and quantification of enantiomers. Using 3,4-dihydroxyphenylalanine (DOPA) as the model analyte, the as-prepared chiral nanofluidic device exhibits a remarkable chiral recognition ability to l-DOPA than d-DOPA. More importantly, due to the chelation of DOPA with Fe3+ ions, it can efficiently block the ion transport through channel and shield the channel surface charge, which will amplify the difference in the electrochemical response of l-DOPA and d-DOPA. Therefore, a sensitive chiral recognition can be achieved using the present nanofluidic device coupled using electrochemical amplification strategy. Notably, using this method, an ultra-low concentration of l-DOPA (as low as 0.21 pM) can be facilely and successfully detected with a linear range of 1 pM-10 μM. This study provides a reliable and sensitive approach for achieving highly selective detection of chiral molecules.

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.

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.

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.

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.

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.

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.

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.

Conducting target ions rapidly while rejecting rival ions efficiently is challenging yet highly demanded for ion separation related applications. Two-dimensional (2D) channels are widely used for ion separation, but highly selective 2D channels generally suffer from a relatively low ionic conductivity. Here we report that the 2D vermiculite channels have a Na+ conductivity higher than bulk and at the same time reject heavy metal ions with a selectivity of a few hundreds. Such performance is attributed to the highly electronegative crystal surface and the extremely narrow channel (0.2 nm high), as also supported by the ab initio molecular dynamics simulation. We demonstrate that the highly selective and conductive sodium channels can be utilized to harvest osmotic power from industrial wastewater, achieving a power density of more than 20 W m-2 while preventing pollution from waste heavy metal ions. This work provides a strategy for wastewater utilization as well as treatment. Moreover, the investigation suggests the possibility to break the ionic permeability-selectivity trade-off by combining Ångstrom-scale confinement with proper surface engineering, which could lead to applications that are challenging for previous materials.