Influence of Interlayer Cation Ordering on Na Transport in P2-Type Na0.67-xLiy Ni0.33-zMn0.67+zO2 for Sodium-Ion Batteries.

P2-type Na2/3Ni1/3Mn2/3O2 (PNNMO) has been extensively studied because of its desirable electrochemical properties as a positive electrode for sodium-ion batteries. PNNMO exhibits intralayer transition-metal ordering of Ni and Mn and intralayer Na+/vacancy ordering. The Na+/vacancy ordering is often considered a major impediment to fast Na+ transport and can be affected by transition-metal ordering. We show by neutron/X-ray diffraction and density functional theory (DFT) calculations that Li doping (Na2/3Li0.05Ni1/3Mn2/3O2, LFN5) promotes ABC-type interplanar Ni/Mn ordering without disrupting the Na+/vacancy ordering and creates low-energy Li-Mn-coordinated diffusion pathways. A structure model is developed to quantitatively identify both the intralayer cation mixing and interlayer cationic stacking fault densities. Quasielastic neutron scattering reveals that the Na+ diffusivity in LFN5 is enhanced by an order of magnitude over PNNMO, increasing its capacity at a high current. Na2/3Ni1/4Mn3/4O2 (NM13) lacks Na+/vacancy ordering but has diffusivity comparable to that of LFN5. However, NM13 has the smallest capacity at a high current. The high site energy of Mn-Mn-coordinated Na compared to that of Ni-Mn and higher density of Mn-Mn-coordinated Na+ sites in NM13 disrupts the connectivity of low-energy Ni-Mn-coordinated diffusion pathways. These results suggest that the interlayer ordering can be tuned through the control of composition, which has an equal or greater impact on Na+ diffusion than the Na+/vacancy ordering.

Tailoring the Coordination Micro-Environment in Nanotraps for Efficient Platinum/Palladium Separation.

Recovering platinum group metals from secondary resources is crucial to meet the growing demand for high-tech applications. Various techniques are explored, and adsorption using porous materials has emerged as a promising technology due to its efficient performance and environmental beingness. However, the challenge lies in effectively recovering and separating individual platinum group metals (PGMs) given their similar chemical properties. Herein, a breakthrough approach is presented by sophisticatedly tailoring the coordination micro-environment in a series of aminopyridine-based porous organic polymers, which enables the creation of platinum-specific nanotraps for efficient separation of binary PGMs (platinum/palladium). The newly synthesized POP-o2NH2-Py demonstrates record uptakes and selectivity toward platinum over palladium, with the amino groups adjacent to the pyridine moieties being vital in improving platinum binding performance. Further breakthrough experiments underline its remarkable ability to separate platinum and palladium. Spectroscopic analysis reveals that POP-o2NH2-Py offers a more favorable coordination fashion to platinum ions compared to palladium ions owing to the greater interaction between N and Pt4+ and stronger intramolecular hydrogen bonding between the amino groups and four coordinating chlorines at platinum. These findings underscore the importance of fine-tuning the coordination micro-environment of nanotraps through subtle modifications that can greatly enhance the selectivity toward the desired metal ions.

Gold(I)-Thiolate Coordination Polymers as Multifunctional Materials: The Case of Au(I)-p-Fluorothiophenolate.

Gold-sulfur interaction has vital importance in nanotechnologies and material chemistry to design functional nanoparticles, self-assembled monolayers, or molecular complexes. In this paper, a mixture of only two basic precursors, such as the chloroauric acid (HAu(III)Cl4) and a thiol molecule (p-fluorothiophenol (p-HSPhF)), are used for the synthesis of gold(I)-thiolate coordination polymers. Under different conditions of synthesis and external stimuli, five different functional materials with different states of [Au(I)(p-SPhF)]n can be afforded. These gold-thiolate compounds are (i) red emissive, flexible, and crystalline fibers; (ii) composite materials made of these red emissive fibers and gold nanoparticles; (iii) amorphous phase; (iv) transparent glass; and (v) amorphous-to-crystalline phase-change material associated with an ON/OFF switch of luminescence. The different functionalities of these materials highlight the great versatility of the gold(I) thiolate coordination polymers with easy synthesis and diverse shaping that may have great potential as sustainable phosphors, smart textiles, sensors, and phase change memories.

Tailoring the d-band center on Ru1Cu single-atom alloy nanotubes for boosting electrochemical non-enzymatic glucose sensing.

The development of cost-effective and highly efficient electrocatalysts is critical to help electrochemical non-enzymatic sensors achieve high performance. Here, a new class of catalyst, Ru single atoms confined on Cu nanotubes as a single-atom alloy (Ru1Cu NTs), with a unique electronic structure and property, was developed to construct a novel electrochemical non-enzymatic glucose sensor for the first time. The Ru1Cu NTs with a diameter of about 24.0 nm showed a much lower oxidation potential (0.38 V) and 9.0-fold higher response (66.5 µA) current than Cu nanowires (Cu NWs, oxidation potential 0.47 V and current 7.4 µA) for glucose electrocatalysis. Moreover, as an electrochemical non-enzymatic glucose sensor, Ru1Cu NTs not only exhibited twofold higher sensitivity (54.9 µA mM-1 cm-2) and wider linear range (0.5-8 mM) than Cu NWs, but also showed a low detection limit (5.0 µM), excellent selectivity, and great stability. According to theoretical calculation results, the outstanding catalytic and sensing performance of Ru1Cu NTs could be ascribed to the upshift of the d-band center that helped promote glucose adsorption. This work presents a new avenue for developing highly active catalysts for electrochemical non-enzymatic sensors.

Toward High-Performance Metal-Organic-Framework-Based Quasi-Solid-State Electrolytes: Tunable Structures and Electrochemical Properties.

Metal-organic frameworks (MOFs) have been reported as promising materials for electrochemical applications owing to their tunable porous structures and ion-sieving capability. However, it remains challenging to rationally design MOF-based electrolytes for high-energy lithium batteries. In this work, by combining advanced characterization and modeling tools, a series of nanocrystalline MOFs is designed, and the effects of pore apertures and open metal sites on ion-transport properties and electrochemical stability of MOF quasi-solid-state electrolytes are systematically studied. It isdemonstrated that MOFs with non-redox-active metal centers can lead to a much wider electrochemical stability window than those with redox-active centers. Furthermore, the pore aperture of MOFs is found to be a dominating factor that determines the uptake of lithium salt and thus ionic conductivity. The ab initio molecular dynamics simulations further demonstrate that open metal sites of MOFs can facilitate the dissociation of lithium salt and immobilize anions via Lewis acid-base interaction, leading to good lithium-ion mobility and high transference number. The MOF quasi-solid-state electrolyte demonstrates great battery performance with commercial LiFePO4 and LiCoO2 cathodes at 30 °C. This work provides new insights into structure-property relationships between tunable structure and electrochemical properties of MOFs that can lead to the development of advanced quasi-solid-state electrolytes for high-energy lithium batteries.

A modulated fingerprint assisted machine learning method for retrieving elastic moduli from resonant ultrasound spectroscopy.

We used deep-learning-based models to automatically obtain elastic moduli from resonant ultrasound spectroscopy (RUS) spectra, which conventionally require user intervention of published analysis codes. By strategically converting theoretical RUS spectra into their modulated fingerprints and using them as a dataset to train neural network models, we obtained models that successfully predicted both elastic moduli from theoretical test spectra of an isotropic material and from a measured steel RUS spectrum with up to 9.6% missing resonances. We further trained modulated fingerprint-based models to resolve RUS spectra from yttrium-aluminum-garnet (YAG) ceramic samples with three elastic moduli. The resulting models were capable of retrieving all three elastic moduli from spectra with a maximum of 26% missing frequencies. In summary, our modulated fingerprint method is an efficient tool to transform raw spectroscopy data and train neural network models with high accuracy and resistance to spectra distortion.

Boosting Electrochemical Catalysis and Nonenzymatic Sensing Toward Glucose by Single-Atom Pt Supported on Cu@CuO Core-Shell Nanowires.

It is critical to develop high-performance electrocatalyst for electrochemical nonenzymatic glucose sensing. In this work, a single-atom Pt supported on Cu@CuO core-shell nanowires (Pt1 /Cu@CuO NWs) for electrochemical nonenzymatic glucose sensor is designed. Pt1 /Cu@CuO NWs exhibit excellent electrocatalytic oxidation toward glucose with 70 mV lower onset potential (0.131 V) and 2.4 times higher response current than Cu NWs. Sensors fabricated using Pt1 /Cu@CuO NWs also show high sensitivity (852.163 µA mM-1 cm-2 ), low detection limit (3.6 µM), wide linear range (0.01-5.18 µM), excellent selectivity, and great long-term stability. The outstanding sensing performance of Pt1 /Cu@CuO NWs, investigated by experiments and density functional theory (DFT) calculations, is attributed to the synergistic effect between Pt single atoms and Cu@CuO core-shell nanowires that generates strong binding energy of glucose on the nanowires. The work provides a new pathway for exploring highly active SACs for electrochemical nonenzymatic glucose sensor.

Single-Atom Pt Boosting Electrochemical Nonenzymatic Glucose Sensing on Ni(OH)2/N-Doped Graphene.

Conventional nanomaterials in electrochemical nonenzymatic sensing face huge challenge due to their complex size-, surface-, and composition-dependent catalytic properties and low active site density. In this work, we designed a single-atom Pt supported on Ni(OH)2 nanoplates/nitrogen-doped graphene (Pt1/Ni(OH)2/NG) as the first example for constructing a single-atom catalyst based electrochemical nonenzymatic glucose sensor. The resulting Pt1/Ni(OH)2/NG exhibited a low anode peak potential of 0.48 V and high sensitivity of 220.75 µA mM-1 cm-2 toward glucose, which are 45 mV lower and 12 times higher than those of Ni(OH)2, respectively. The catalyst also showed excellent selectivity for several important interferences, short response time of 4.6 s, and high stability over 4 weeks. Experimental and density functional theory (DFT) calculated results reveal that the improved performance of Pt1/Ni(OH)2/NG could be attributed to stronger binding strength of glucose on single-atom Pt active centers and their surrounding Ni atoms, combined with fast electron transfer ability by the adding of the highly conductive NG. This research sheds light on the applications of SACs in the field of electrochemical nonenzymatic sensing.

Building bimodal structures by a wettability difference-driven strategy for high-performance protein air-filters.

Building bimodal structures for air-filters is promising to reduce the airflow resistance without sacrificing the filtration efficiency. To do so, multi-jet electrospinning is among the most broadly used methods, yet the interplay between single fibers in electrospinning, which is significant to their morphologies, is overlooked. In this study, we report a wettability difference-driven strategy to fabricate a bimodal protein fabric with superior filtration performance. We surprisingly find that only by co-spinning of two proteins, zein and gelatin, with different wettability between them, a drastic change of fiber diameters is spontaneously achieved. The generated protein-blend fabric possesses bimodally distributed diameters of 270 nm for gelatin fibers and of 1.12 µm for zein fibers; both pure protein fabrics via single-jet electrospinning have diameters unimodally distributed in the range of 500-700 nm. The bimodal protein-blend fabric delivers exceptional removal efficiencies of 99.67% for PM2.5 and 98.80% for PM0.3, yielding an ultra-low airflow resistance of 38 Pa. The PM2.5 removal efficiency retains to be 96.04% after filtering 1000 L polluted air, indicating a good long-term performance. This study brings about a new insight into fabrication of bimodal structures using multi-jet electrospinning method and promotes the development of natural products for broad applications.

A Bimodal Protein Fabric Enabled via In Situ Diffusion for High-Performance Air Filtration.

Design and fabrication of bimodal structures are essential for successful development of advanced air filters with ultralow airflow resistance. To realize this goal, simplified processing procedures are necessary for meeting the practical needs. Here, a bimodal protein fabric with high-performance air filtration, and effectively lowered airflow resistance is reported. The various functional groups of proteins provide versatile interactions with pollutants. By utilizing a novel and cost-effective "cross-axial" configuration with an optimized condition (75° of contacting angle between solution nozzle and cospinning solvent nozzle), the diffusion in Taylor cone is in situ controlled, which results in the successful production of bimodal protein fabric. The bimodal protein fabric (16.7 g/m2 areal density) is demonstrated to show excellent filtration performance for removing particulate matter (PM) pollutants and only causes 17.1 Pa air pressure drop. The study of multilayered protein fabric air filters shows a further improvement in filtration performance of removing 97% of PM0.3 and 99% of PM2.5 with a low airflow resistance (34.9 Pa). More importantly, the four-layered bimodal protein fabric shows an exceptional long-term performance and maintains a high removal efficiency in the humid environment. This study presents an effective and viable strategy for fabricating bimodal fibrous materials for advanced air filtration.

A Super-breathable "Woven-like" Protein Nanofabric.

Nanofabrics made from abundant natural protein that possesses enormous amounts of functional groups may have important applications such as air filtration. However, protein nanofabrics with randomly distributed nanofibers have very low mechanical properties and high airflow resistance, both of which seriously reduce the breathability. Here, a super-breathable zein (corn protein) fabric having a unique "woven-like" nanofibrous structure (w-PNF) via the accumulation effect between the charged nanofibers and the collector during electrospinning is reported. The resulting w-PNF exhibits remarkable tensile strength and modulus, which are 3 and 9 times, respectively, higher than the random protein nanofibrous materials. The filtration tests indicate that w-PNF presents super-breathable performance, including ultralow airflow resistance (1/12 of that of the nonwoven nanofabric) and high filtration efficiency for capturing PM2.5. As compared with the reported nanofabrics, w-PNF maintains the same airflow resistance at up to 4 times higher airflow rate. In addition, w-PNF presents visible-light transparency (80%) and high resolution even in microareas. This work provides a significant strategy for designing and fabricating nanofabrics for boosting the development of biological nanomaterials.