Highly Selective Transmembrane Transport of Exogenous Lithium Ions through Rationally Designed Supramolecular Channels

Lithium ions have been applied in the clinic in the treatment of psychiatric disorders. In this work, we report artificial supramolecular lithium channels composed of pore-containing small aromatic molecules. By adjusting the lumen size and coordination numbers, we found that one of the supramolecular channels developed shows unprecedented transmembrane transport of exogenous lithium ions with a Li⁺/Na⁺ selectivity ratio of 23.0, which is in the same level of that of natural Na⁺ channels. Furthermore, four coordination sites inside channels are found to be the basic requirement for ion transport function. Importantly, this artificial lithium channel displays very low transport of physiological Na⁺, K⁺, Mg²⁺, and Ca²⁺ ions. This highly selective Li⁺ channel may become an important tool for studying the physiological role of intracellular lithium ions, especially in the treatment of psychiatric disorders.     

Hydrogen Bond Networks Stabilized High-Capacity Organic Cathode for Lithium-Ion Batteries

High-capacity small organic materials are plagued by their high solubility. Here we proposed constructing hydrogen bond networks (HBN) via intermolecular hydrogen bonds to suppress the solubility of active material. The illustrated 2, 7- diamino-4, 5, 9, 10-tetraone (PTO-NH₂) molecule with intermolecular hydrogen (H) bond between O in −C=O and H in −NH₂, which make PTO-NH₂ presents transverse two-dimensional extension and longitudinal π–π stacking structure. In situ Fourier transform infrared spectroscopy (FTIR) has tracked the reversible evolution of H-bonds, further confirming the existence of HBN structure can stabilize the intermediate 2-electron reaction state. Therefore, PTO-NH₂ with HBN structure has higher active site utilization (95 %), better cycle stability and rate performance. This study uncovers the H-bond effect and evolution during the electrochemical process and provides a strategy for materials design.     

Unraveling the Oxidation Behaviors of MXenes in Aqueous Systems by Active-Learning-Potential Molecular-Dynamics Simulation

MXenes are 2D materials with great potential in various applications. However, the degradation of MXenes in humid environments has become a main obstacle in their practical use. Here we combine deep neural networks and an active learning scheme to develop a neural network potential (NNP) for aqueous MXene systems with ab initio precision but low cost. The oxidation behaviors of super large aqueous MXene systems are investigated systematically at nanosecond timescales for the first time. The oxidation process of MXenes is clearly displayed at the atomic level. Free protons and oxides greatly inhibit subsequent oxidation reactions, leading to the degree of oxidation of MXenes to exponentially decay with time, which is consistent with the oxidation rate of MXenes measured experimentally. Importantly, this computational study represents the first exploration of the kinetic process of oxidation of super-sized aqueous MXene systems. It opens a promising avenue for the future development of effective protection strategies aimed at controlling the stability of MXenes.     

A Dissipative Reaction Network Drives Transient Solid–Liquid and Liquid–Liquid Phase Cycling of Nanoparticles

Transient states maintained by energy dissipation are an essential feature of dynamic systems where structures and functions are regulated by fluxes of energy and matter through chemical reaction networks. Perfected in biology, chemically fueled dissipative networks incorporating nanoscale components allow the unique properties of nanomaterials to be bestowed with spatiotemporal adaptability and chemical responsiveness. We report the transient dispersion of gold nanoparticles in water, powered by dissipation of a chemical fuel. A dispersed state that is generated under non-equilibrium conditions permits fully reversible solid–liquid or liquid–liquid phase transfer. The molecular basis of the out-of-equilibrium process is reversible covalent modification of nanoparticle-bound ligands by a simple inorganic activator. Activator consumption by a coupled dissipative reaction network leads to autonomous cycling between phases. The out-of-equilibrium lifetime is tunable by adjusting the pH value, and reversible phase cycling is reproducible over several cycles.     

Tin(II)-Based Metal–Organic Frameworks Enabling Efficient,Selective Reduction of CO2 to Formate under Visible Light

Certain metal complexes are known as high-performance CO₂ reduction photocatalysts driven by visible light. However, most of them rely on rare, precious metals as principal components, and integrating the functions of light absorption and catalysis into a single molecular unit based on abundant metals remains a challenge. Metal-organic frameworks (MOFs), which can be regarded as intermediate compounds between molecules and inorganic solids, are potential platforms for the construction of a simple photocatalytic system composed only of Earth-abundant nontoxic elements. In this work, we report that a tin-based MOF enables the conversion of CO₂ into formic acid with a record high apparent quantum yield (9.8 % at 400 nm) and >99 % selectivity without the need for any additional photosensitizer or catalyst. This work highlights a new MOF with strong potential for photocatalytic CO₂ reduction driven by solar energy.     

Mechano-Activated Self-Immolation of Hydrogels via Signal Amplification

Cellular organisms possess intricate mechano-adaptive systems that enable them to sense forces and process them with (bio)chemical circuits for functional adaptation. Inspired by such processes, this study introduces a hydrogel system capable of mechanically activated and chemically transduced self-destruction. Our judiciously designed hydrogels can mechanically generate radicals that are processed and amplified in a self-propagating radical de-crosslinking reaction, ultimately leading to mechanically triggered self-immolation. We put such systems to work in mechano-induced debonding, and in a bilayer actuator, where swelling-induced bending generates sufficient force for selective degradation of one layer, leading to autonomous self-regulation associated with unbending. Our work helps define design criteria for molecularly controlled adaptive and self-regulating materials with embodied mechano-chemical information processing, and showcases their potential for adhesives and soft robotics.     

In-Situ Constructing A Heterogeneous Layer on Lithium Metal Anodes for Dendrite-Free Lithium Deposition and High Li-ion Flux

Constructing efficient artificial solid electrolyte interface (SEI) film is extremely vital for the practical application of lithium metal batteries. Herein, a dense artificial SEI film, in which lithiophilic Zn/Li_xZn_y are uniformly but nonconsecutively dispersed in the consecutive Li⁺-conductors of Li_xSiO_y, Li₂O and LiOH, is constructed via the in situ reaction of layered zinc silicate nanosheets and Li. The consecutive Li⁺-conductors can promote the desolvation process of solvated-Li⁺ and regulate the transfer of lithium ions. The nonconsecutive lithiophilic metals are polarized by the internal electric field to boost the transfer of lithium ions, and lower the nucleation barrier. Therefore, a low polarization of ≈50 mV for 750 h at 2.0 mA cm⁻² in symmetric cells, and a high capacity retention of 99.2 % in full cells with a high lithium iron phosphate areal loading of ≈13 mg cm⁻² are achieved. This work offers new sights to develop advanced alkali metal anodes for efficient energy storage.     

Highly Reproducible Flexible Ion-selective Electrodes for the Detection of Sodium and Potassium in Artificial Sweat

It is well known that potentiometric sensors provide a versatile, cost-effective, and efficient platform for wearable applications. Unfortunately, mass production and commercialization of such devices is often constrained by the requirement of a calibration step, which is due to the poor sensor-to-sensor reproducibility and the need of conditioning the electrodes in the analyte before use. Herein, we fabricated calibration-free flexible sensors including ion-selective electrode and reference electrode by integrating single-walled carbon nanotubes (SWCNTs) with poly(3-octylthiophene) (POT) and applying on polyethylene terephthalate (PET) substrate. The developed sodium and potassium ion-selective electrodes (ISEs) display excellent repeatability, selectivity, stability as well as high sensor-to-sensor reproducibility, with a standard deviation of as low as 1.0 mV in artificial sweat microliter samples volume.     

Application of an artificial neural network (ANN) and piezoelectric chemical sensor array for identification of volatile organic compounds

A piezoelectric chemical sensor array was developed using four quartz crystals. Gas chromatographic stationary phases were used as sensing materials and the array was connected to an artificial neural network (ANN). The application of the ANN method proved to be particularly advantageous if the measured property (mass, concentration, etc.) should not be connected exactly to the signal of the transducers of the piezoelectric sensor. The optimum structure of neural network was determined by a trial and error method. Different structures were tried with several neurons in the hidden layer and the total error was calculated. The optimum values of primary weight factors, learning rate (η=0.15), momentum term (μ=0.9), and the sigmoid parameter (β=1) were determined. Finally, three hidden neurons and 900 training cycles were applied. After the teaching process the network was used for identification of taught analytes (acetone, benzene, chloroform, pentane). Mixtures of organic compounds were also analysed and the ANN method proved to be a reliable way of differentiating the sensing materials and identifying the volatile compounds.