Biological ion channels exhibit exceptional capabilities in regulating ion transport across cell membranes, which is essential for numerous physiological functions. Researchers are particularly interested in investigating ion transport through nanopores and nanochannels because of their similarity to biological ion channels. Graphene has gained attention as a promising membrane material, not only for its strength, stability, and high permeability, but also for its remarkable electrical conductivity, which enables active regulation of ion transport through nanopores via an applied gate voltage (V-g). In this study, a composite nanochannel was created using swift heavy ion (SHI) irradiation on single-layer graphene (SLG) and multi-layer graphene (MLG) combined with polyethylene terephthalate (PET). An external gate voltage was applied to modulate ion transport. Significantly enhanced ion permeation was observed under negative V-g (e.g., -0.7 V), particularly for SLG/PET membranes, exhibiting higher K+ permeation flux (1.6 x 10(-5) mol cm(-2) h(-1)) and a competitive K+/Mg2+ selectivity ratio of similar to 5, compared to MLG/PET (9.2 x 10(-6) mol cm(-2) h(-1)). This modulation is attributed to voltage-induced changes in the electric double layer (EDL) structure and surface potential of graphene. These results demonstrate that V-g enables electrostatic control over the transport of ions, including K+, Na+, Mg2+, and SO42-. Voltage gating induces ion accumulation or depletion near the nanopores, effectively modulating cation transport dynamics. These findings confirm the ability of voltage-gated graphene nanopores to dynamically modulate ion transport behavior, achieving enhanced selectivity for monovalent over divalent cations. This work provides a foundation for designing tunable nanoporous membranes for applications in energy conversion, ion separation, and nanofluidics.

Efficient extraction of lithium-ion from salt-lake brine remains a significant challenge, primarily due to the similar physicochemical properties of Li+ and Mg2+, and the inherent trade-off between permeability and selectivity in conventional membrane processes. Herein, we propose a synergistic membrane-solution strategy that integrates an enlarged sub-nanoporous polyimide membrane (ESN-PI) with ethylenediaminetetraacetate (EDTA(4-)) complexation to enhance the Li+ flux and Li+/Mg2+ selectivity simultaneously. The ESN-PI membrane, fabricated via heavy-ion irradiation and controlled alkaline etching, provides enlarged transport channels that significantly improve Li+ permeation. Meanwhile, EDTA(4-) selectively chelates Mg2+ to form a bulky, negatively charged [EDTA-Mg](2-) complex, which is electrostatically repelled and sterically hindered by the negatively charged sub-nanopores, thereby greatly suppressing Mg2+ transmembrane transport. The coupled system delivers a high Li+ flux of up to 73 mmol h(-1) m(-2) and an exceptional Li+/Mg2+ selectivity of 351. Notably, the separation performance remains robust (selectivity > 300) even at a high feed Mg2+/Li+ ratio of 60, and EDTA(4-) can be efficiently regenerated and reused over multiple cycles. This research utilized heavy ion irradiation technology to prepare a more economical cation exchange membrane. By coupling the membrane with the EDTA complexation strategy, it was able to resolve the contradiction between permeability and selectivity in the ion separation process based on the membrane, providing a promising strategy for extracting lithium from brines with high magnesium ion content.

The physical separation of memory and processing in conventional architectures results in significant energy dissipation during data movement. This has motivated research into brain-inspired information processing, where memory and learning are realized in a single unit using water and ions. Herein, we report biomimetic memristive and synaptic-like ion dynamics in an aqueous environment using ion-track etched smart nanochannels. Our experiments demonstrate that driving ions through asymmetric bipolar surface charges generates a memristive effect capable of withstanding hours of endurance stress, and that the memristor type can be dynamically changed by the local chemical environment due to counterion over-screening. We identify ion accumulation and depletion as the single unifying mechanism underlying both memristive switching and synaptic plasticity. These controllable ion dynamics emulate a broad spectrum of plasticity: from short-term plasticity to long-term potentiation and depression (LTP/LTD) with near-linear, low-asymmetry conductance modulation and a low energy consumption of 13.2 pJ per synaptic event. Implementing these reversible weight updates in artificial neural network (ANN) simulations yields a recognition accuracy of 94.54% for handwritten digit recognition (small-digit MNIST), rivaling solid-state memristors. These findings demonstrate that systematic control of ion interactions within nanochannels provides a high-performance, energy-efficient foundation for neuromorphic computing.

Lightweight polymer-based Al composite current collectors (Al CCCs) are promising for reducing inactive mass in lithium-ion batteries, but the relationships among sputtering parameters, microstructure, defects, adhesion, and high-voltage corrosion stability remain insufficiently understood. Herein, symmetric Al/PET/Al CCCs were fabricated by DC magnetron sputtering on both sides of an 8 μm PET substrate, with each Al layer controlled to approximately 1 μm. By varying sputtering power from 10 to 250 W, power-dependent film growth, corrosion resistance, adhesion, and electrochemical stability were systematically investigated. Increasing sputtering power promoted Al island coalescence, film densification, crystallographic ordering, and strain relaxation. Surface porosity decreased from 0.38% at 10 W to 0.17% at 200 W, while the lowest roughness was obtained at 200 W. However, excessive power caused local surface heterogeneity and roughening. Intermediate sputtering powers, especially 150 W, produced a balanced film state with compact morphology, low surface oxidation, strong adhesion, and reduced corrosion tendency. In LiFePO4||Li cells operated at 2.4–4.2 V, all samples showed similar cycling behavior. In high-voltage LiNi0.5Mn1.5O4||Li cells operated at 3.0–4.9 V, the 150 W coating delivered superior stability, retaining 85.6 mAh g−1 after 500 cycles. These results highlight the importance of optimizing the sputtering-growth window for polymer-supported Al CCCs.

Hydrophilicity is an important property for membranes as it influences the application scope and effectiveness of separation process, and various surface modification methods have been developed targeting to an enhanced hydrophilicity. However, few work focuses on hydrophilicity tunability, and many researches can only obtain limited wettability improvement. Here, a novel surface modification method is reported. In this method, surface functional groups on polyethylene terephthalate membrane are activated and hydrophilic polyethylenimine chains can be grafted to the membrane in a layer-by-layer manner. The membrane hydrophilicity is thus tunable in a wide range through adjusting the number of grafting steps, and a water contact angle decrease of 54 degrees that exceeds most of other grafting modification methods is achieved. Optimal membrane hydrophilicity corresponding to a contact angle of 60 degrees is found through the screening for the highest water permeability, and a water permeability improvement of similar to 29 % is observed for modified PET track-etched membranes with different parameters.

A systematic understanding of the mechanism in the rectification and capacitance of nanochannels and their regulation with the electrolyte concentration and electrical bias is pivotal for its wide applications to nanofluidic electronics, ion separation, energy storage, and molecule sensing. Single unipolar and bipolar cylindrical nanochannels through polymer film were fabricated using single ion bombardment and track etching. Cyclic voltammetry results show that the bipolar nanochannel switches from rectification to capacitance as the electrolyte concentration decreases. Electrochemical impedance spectroscopy revealed that the capacitive impedance fraction in the bipolar nanochannel is regulated by electrolyte concentration and voltage. The switch from rectification to capacitance in the polymer nanochannel is well explained through a fluidic p-n junction model with a variable ion depletion layer regulated by the applied bias voltage, which is supported by the multi-physics simulation using Poisson-Nernst-Planck and Navier-Stokes solution. This work provides a mechanistic insight into the ionic current rectification and ionic capacitance in complex ionic nanochannels and paves the way for biomimetic nanofluidic electronics design.

Colloid interactions are usually interpreted using the classic Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and its variants. However, the repulsive interaction energy given in some DLVO predictions was sometimes inconsistent with the observed aggregation in heterogeneous colloidal systems containing different types of colloids. To address this issue, we studied the heteroaggregation of silica and goethite colloids, two oppositely charged colloids commonly found in the environment, as functions of colloid mass ratio, pH and ionic strength. We found that the discrepancies between experimental observations and DLVO predictions can be attributed to the heterogeneous surface charge distributions of the primary aggregates, contradicting the DLVO assumption of homogeneously charged primary aggregates. Consequently, a new method considering the effect of heterogeneity, was developed to quantitatively evaluate the interaction energies between primary heteroaggregates based on the electrostatic and van der Waals interactions (Hetero-DLVO). The interaction energies, evaluated by considering all pairwise interactions among the component colloids of the two primary aggregates (i.e., silica-silica, goethite-goethite, and silica-goethite), showed good agreement with experimental observations under various conditions. This study contributes to a better understanding of heteroaggregation mechanisms, improved DLVO-based prediction strategies for heterogeneous colloidal systems, and facilitates accurate predictions of colloidal particle behavior in aquatic systems.

The separator plays an important role in transporting ions and preventing thermal runaway, which affects the safety of lithium-ion batteries (LIBs). Herein, a novel aluminum oxide-modified polyethylene terephthalate-based track-etched membrane (Al2O3/PETTEM) separator is fabricated through a combination of heavy-ion track etching and vacuum filtration methods to regulate lithium-ion transport and improve the safety of LIBs. The separator features a hierarchical nanochannel structure composed of the vertically aligned channels in PETTEM and the gaps between Al2O3 nanoparticles on the PETTEM surface, which facilitates the rapid transport and uniform deposition of lithium ions. As a result, the Li||Li cell with the Al2O3/PETTEM separator achieves an extended cycle lifespan of up to 1000 h at 0.5 mA cm-2. The LFP||Li cell with the Al2O3/PETTEM separator exhibits a high initial discharge specific capacity of 143 mA h g-1 and maintains 94 % capacity after 200 cycles at room temperature. Additionally, after being modified with Al2O3 nanoparticles, the separator exhibits enhanced thermal stability, enabling stable battery operation at an elevated temperature of up to 120 degrees C and retaining 93.3 % capacity after 200 cycles. This work can offer promising strategies for developing high-safety LIBs.

Efficient extraction and separation of actinium-225 (225Ac) are critical to meeting the growing global demand for its radiopharmaceutical applications. However, the conventional technologies remain many drawbacks, like excessive consumption of chemical reagents, production of significant quantities of secondary radioactive waste, and complex purification procedures. To address these challenges, an innovative membrane-based separation strategy was developed. Considering the short half-life (t1/2 = 9.92 d) and high radioactivity of 225Ac, lanthanum was selected as a surrogate for systematic investigation in this work, which has similar physicochemical properties to 225Ac and is without radioactive activity. Here, a graphene oxide (GO) membrane intercalated with graphene oxide quantum dots (GOQDs) is designed, enabling highly selective separation and efficient recovery of lanthanum. This work exploits differences in hydrated ionic radii through the precise modulation of interlayer spacing, demonstrating superior separation performance under practical conditions. After three consecutive filtration cycles, the membrane demonstrates a lanthanum recovery rate of 94.88 % and a lanthanum-thorium separation factor of 32.16. This work introduces a sustainable and cost-effective membrane-based lanthanum recovery technology, offering a promising pathway for 225Ac purification and its subsequent application in radiopharmaceutical production.

Membranes with angstrom-sized channels can enable precise ion separation. While progress has been achieved in polymer membranes, which are the dominant commercial membranes, significant technical challenges of creating angstrom-sized channels remain in these membranes. Here, we report an ultraviolet-water (UV-W) strategy to create angstrom-sized channels (2.9-7.8 Å) with tunable size and charges in ion-tracked polymer membranes, where 'UV-W' refers to water illuminated by ultraviolet light, which is able to generate highly oxidative hydroxyl radicals. These generated hydroxyl radicals can scissor polymer chains within the ion tracks. Thus, we first create water passages within the polymer, then with the aid of hydroxyl radicals we subsequently form transport channels. The resultant membrane exhibits outstanding separation performance with a Li+ permeation rate of 0.3 mol m-2 h-1 and Li+/Mg2+ selectivity of 1024, which surpassed the performance of the existing polymer membranes. This easy approach provides an avenue for developing angstrom-sized channels in diverse polymers, offering broad application potential in clean energy fields.

Memory and learning in biological systems arise from ion transport across nanoscale synaptic junctions in neural networks. These junctions act as a natural memristors and thus, reproducing this effect in artificial aqueous systems is crucial for mimicking neural functions and advancing neuromorphic computing. Herein, we successfully demonstrated the memristive effects through the spatial confinement of water and ions within a biomimetic nanochannel, using two distinct stimulation mechanisms (i) divalent-ion screening and (ii) pH-driven deprotonation. In both cases, broken symmetry within the medium coupled with surface effects, lead to hysteretic ion transport. This nanofluidic memristor also emulated biological memory features, including both short/long-term potentiation and key synaptic functionalities, such as paired-pulse facilitation (PPF) and paired-pulse depression (PPD). The reversible modulation of ionic conductance of our nanofluidic device enabled dynamic encoding of synaptic weights, a key mechanism underlying adaptive learning behavior in neuromorphic systems. Leveraging this property, a three-layer artificial neural network for pattern recognition is trained and recognition accuracy of 94.6% on the small-digit MNIST dataset, which can compete with the performance of many solid-state memristive synapses. The memory effect resemblance between our single-channel system to biological counterparts, paves the way for elucidating the origin of memory in biological systems and advancing nanofluidic memristor-based neuromorphic computing.

Ion separation has great potential in a variety of applications, including water treatment, energy conversion, and resource recovery. The sub-nanoporous polymeric membranes prepared by track-UV method has good prospects for ion separation. However, the ion selectivity of reported sub-nanoporous membranes is still not ideal. In this study, we prepared sub-nanoporous polyetherimide membranes. The sub-nanometer gaps on the membrane exhibit a unique monovalent ion selective transport. The selectivity attributes to the dehydration energy barrier of ions and the interaction between ions and surface charge. The single salt electrodialysis experiments showed that the ideal selectivity of K+/Mg2+ was as high as 8900, and the potassium ion flux was 0.49 mol h-1 m- 2. In addition, the membrane showed a K+/Li+ selectivity of up to 6 and a K+/Mg2+ selectivity of 67 under mixed salt conditions. This work provides a valuable insight into the future large-scale and expedited production of subnanoporous membranes featuring exceptional ion separation performance.

Separators play a crucial role in inhibiting thermal runaway in lithium-ion batteries (LIBs). In this study, the doctor blade coating method and heavy-ion track etching technology were used to prepare a polyimide-based covalent organic framework (PI_COF) separator with excellent thermal stability and a long cycle life. Specifically, COF300 was simply coated on the surface of a polyimide-based track-etched membrane (PI_TEM) with straight through holes, which provided a rigid framework and high-temperature stability at 300 degrees C. These features were conducive to inhibiting thermal runaway, while porous COF300 with large holes increased the wettability of the electrolyte, facilitating lithium-ion migration and suppression of lithium dendrite growth; consequently, LIBs with an excellent cycling performance and a high rate capacity were obtained. The cell with the PI_COF separator delivered a high capacity of 90.0 mA h g(-1) after 1000 cycles. The PI_COF separator with high thermal stability exhibited a long cycle life in LIBs. These features are beneficial for improving the safety characteristics of LIBs as well as for accelerating the practical application process of the PI_COF separator.

Separator is an essential component of lithium-ion batteries (LIBs), playing a pivotal role in battery safety and electrochemical performance. However, conventional polyolefin separators suffer from poor thermal stability and nonuniform pore structures, hindering their effectiveness in preventing thermal shrinkage and inhibiting lithium (Li) dendrites. Herein, we present a robust, high-temperature-resistant polyimide (PI) separator with vertically aligned uniform nanochannels, fabricated via ion track-etching technology. The resultant PI track-etched membranes (PITEMs) effectively homogenize Li-ion distribution, demonstrating enhanced ionic conductivity (0.57 mS cm-1) and a high Li+ transfer number (0.61). PITEMs significantly prolong the cycle life of Li/Li cells to 1200 h at 3 mA cm-2. For Li/LiFePO4 cells, this approach enables a specific capacity of 143 mAh g-1 and retains 83.88% capacity after 300 cycles at room temperature. At 80 degrees C, the capacity retention remains at 85.92% after 200 cycles. Additionally, graphite/LiFePO4 pouch cells with PITEMs display enhanced cycling stability, retaining 73.25% capacity after 1000 cycles at room temperature and 78.41% after 100 cycles at 80 degrees C. Finally, PITEMs-based pouch cells can operate at 150 degrees C. This separator not only addresses the limitations of traditional separators, but also holds promise for mass production via roll-to-roll methods. We expect this work to offer insights into designing and manufacturing of functional separators for high-safety LIBs.

Lithium (Li) metal anodes have received sustained attention due to their remarkable theoretical specific capacities and low electrochemical potentials. However, the nucleation and growth of Li dendrites during cycling have hindered their application in Li metal batteries (LMBs). As an indispensable battery component, separators offer an ideal platform for mitigating Li dendrites. Herein, an ion‐management membrane (IMM) concept utilizing polydopamine (PDA)‐modified polyetherimide track‐etched membranes (PEITEMs) is proposed. The PDA@PEITEM‐based IMM features vertically aligned uniform electronegative nanochannels, serving as ion distributors and “Li‐ion guides” to simultaneously smooth ion concentration fluctuations and accelerate Li+ selective conduction. The IMM's unique structural and chemical properties yield exceptional ionic conductivity (0.73 mS cm−1) and high Li+ transfer number (0.80) while minimizing Li+ concentration fluctuations. When employed in Li/Cu cells, the IMM facilitates a Coulombic efficiency exceeding 96% over 100 cycles at 0.5 mA cm−2. Moreover, it extends the cycle lifespan of Li/Li cells to 1 200 h at 1.0 mA cm−2. For Li/LiFePO4 cells, this approach enables a specific capacity of 146 mAh g−1, maintaining capacity retention of 79.84% after 1 000 cycles. This novel strategy for constructing free‐standing functional separators is convenient, efficient, and scalable, providing valuable insights into multifunctional separators for dendrite‐free LMBs.

DAMPE space-borne cosmic ray experiment has been collecting data since December 2015. Many high-impact results on the ion, electron and photon fluxes were obtained. This submission presents the carbon flux analysis with DAMPE using machine learning techniques. The readout electronics would saturate at energy deposits above several TeV in a single BGO bar of the DAMPE calorimeter. The total energy loss per event due to saturation can sometimes reach over a hundred TeV. We present a convolutional neural network model which can accurately recover the energy lost due to saturation and thus significantly increase the dynamic range of DAMPE. Another machine learning model combines the resolution of the hodoscopic BGO calorimeter and the high-resolution tracker of DAMPE to provide the best possible prediction of the direction of the incoming particle. This allows measuring charges at energies up to several hundred TeV. In this work, we present the application of these methods to carbon flux analysis.

The DArk Matter Particle Explorer (DAMPE) is a satellite-borne experiment, in operation since 2015, aimed at studying cosmic rays and high-energy gamma rays. Proton and helium are the first-and second-most abundant components in cosmic rays. Given their smaller interaction cross sections with the interstellar medium, compared to heavier nuclei, they can travel larger distances, thereby becoming important probes to cosmic-ray sources as well as acceleration and propagation mechanisms. Recently, in the DAMPE collaboration, machine learning (ML) techniques were developed and deployed to improve particle tracking and identification and correct for the calorimeter readout saturation at high energies. This work presents a direct measurement of the energy spectra of cosmic-ray protons and helium nuclei, using 84 and 81 months of data, respectively, recorded by DAMPE. Application of the above-mentioned ML techniques helps in extending the spectra to higher kinetic energies than those previously reported by DAMPE

The DArk Matter Particle Explorer (DAMPE) is a space-borne high-energy particle detector launched on 17 December 2015. It can observe the $\gamma$-ray sky from $\sim 2$ GeV to 10 TeV with the acceptance at most $1800~\rm cm^2\,sr$. With over 7.5 years of continuous operation, DAMPE has surveyed the whole sky for about 15 times and collected more than 300,000 candidate photon events. In the last few years, the understanding of the payload has been improved and the instrumental response functions have been calibrated with the on-board data. Besides, progresses have been made on the $\gamma$-ray line search, point source detection, diffuse emission analysis, and transient source monitoring. In the talk and this accompanying proceeding, the latest results on these topics are reported.

The Dark Matter Particle Explorer (DAMPE) is a space-based Cosmic Ray (CR) observatory with the aim, among others, to study Cosmic Ray Electrons (CREs) up to 10 TeV. Due to the low CRE rate at multi-TeV range, we aim at increasing the acceptance by selecting events outside the fiducial volume. The complex topology of non-fiducial events require special treatment with sophisticated analysis tools. Therefore, we propose a Convolutional Neural Network (CNN) to identify non-fiducial CREs and reject background events, based on their interaction in DAMPE's calorimeter. In the following, we will present the aforementioned method in order to precisely identify such events.

Surface-enhanced Raman spectroscopy (SERS), with highsensitivityto a broad range of molecules, can detect molecular "fingerprints"in a complex substance and thereby offers a promising solution fornoninvasive medical diagnostics and personal healthcare monitoring.The eventual realization of such applications relies on SERS substrateswith dense and uniform hot spots, good chemical stability, and highmechanical durability. With these criteria in mind, we developed aflexible nanoporous SERS substrate via the in situ synthesis of goldnanostars (AuNSs) on an ion-track-etched polycarbonate membrane. Thenanoporous SERS substrate can realize analyte enrichment and exhibitexcellent Raman performance by taking the advantage of hot spots onAuNSs. The SERS substrate yields highly repeatable and uniform signalsfor analytes (e.g., methylene blue) over a wide concentration rangefrom 10(-4) to 10(-13) M. The flexibleSERS substrate even can work well after 2000 times bending and exhibitexcellent stability for long-term use. It can be prepared on a largescale with a low-cost and simple fabrication process and can be usedrepeatedly after cleaning to reduce the use-cost further. On-bodyexperiments prove that the sweat SERS substrate allows effective identificationof sweat contents, such as lactic acid and uric acid (UA), and themonitoring of diet-induced variation in sweat UA. The potential ofthe wearable nanoporous SERS substrates in sweat analysis thus hasbeen demonstrated, opening possibilities for autonomous and noninvasivemedical health monitoring.