Steric hindrance modulation of hexaazatribenzanthraquinone isomers for high-capacity and wide-temperature-range aqueous proton battery.

Organic materials with rich active sites are good candidates of high-capacity anodes in aqueous batteries, but commonly low utilization of active sites limits their capacity. Herein, two isomers, symmetric and asymmetric hexaazatribenzanthraquinone (s-HATBAQ and a-HATBAQ), with rich active sites have been synthesized in a controllable manner. It has been revealed for the first time that a sulfuric acid catalyst can facilitate the stereoselective formation of s-HATBAQ. Attributed to the reduced steric hindrance in favor of proton insertion as well as the amorphous structure conducive to electrochemical dynamics, s-HATBAQ exhibits 1.5 times larger specific capacity than a-HATBAQ. Consequently, the electrode of s-HATBAQ with 50% reduced graphene oxide (s-HATBAQ-50%rGO) delivers a record high specific capacity of 405 mAh g-1 in H2SO4 electrolyte. Moreover, the assembled MnO2//s-HATBAQ-50%rGO aqueous proton full batteries show an exceptional cycling stability at 25°C and can maintain ∼92% capacity after 1000 cycles at 0.5 A g-1 at -80°C. This work demonstrates the controllable synthesis of isomers, showcases a wide-temperature-range prototype proton battery and highlights the significance of precise molecular structure modulation in organic energy storage.

Computational screening and functional tuning of chemically stable metal organic frameworks for I2/CH3I capture in humid environments.

High chemical stability is of vital significance in rendering metal organic frameworks (MOFs) as promising adsorbents for capturing leaked radioactive nuclides, under real nuclear industrial conditions with high humidity. In this work, grand canonical Monte Carlo (GCMC) and density functional theory (DFT) methods have been employed to systematically evaluate I2/CH3I capture performances of 21 experimentally confirmed chemically stable MOFs in humid environments. Favorable structural factors and the influence of hydrophilicity for iodine capture were unveiled. Subsequently, the top-performing MIL-53-Al with flexible tunability was functionalized with different functional groups to achieve the better adsorption performance. It has been revealed that the adsorption affinity and pore volume were two major factors altered by the functionalization of polar functional groups, which collectively influenced the iodine adsorption properties. In general, this work has screened the chemically stable high-performance MOF iodine adsorbents and provided comprehensive insights into the key factors affecting I2/CH3I uptake and separation in humid environments.

Recent Advances in Flexible Pressure Sensors Based on MXene Materials.

In the past decade, with the rapid development of wearable electronics, medical health monitoring, the Internet of Things, and flexible intelligent robots, flexible pressure sensors have received unprecedented attention. As a very important kind of electronic component for information transmission and collection, flexible pressure sensors have gained a wide application prospect in the fields of aerospace, biomedical and health monitoring, electronic skin, and human-machine interface. In recent years, MXene has attracted extensive attention because of its unique 2D layered structure, high conductivity, rich surface terminal groups, and hydrophilicity, which has brought a new breakthrough for flexible sensing. Thus, it has become a revolutionary pressure-sensitive material with great potential. In this work, the recent advances of MXene-based flexible pressure sensors are reviewed from the aspects of sensing type, sensing mechanism, material selection, structural design, preparation strategy, and sensing application. The methods and strategies to improve the performance of MXene-based flexible pressure sensors are analyzed in details. Finally, the opportunities and challenges faced by MXene-based flexible pressure sensors are discussed. This review will bring the research and development of MXene-based flexible sensors to a new high level, promoting the wider research exploitation and practical application of MXene materials in flexible pressure sensors.

A novel registration method for long-serial section images of EM with a serial split technique based on unsupervised optical flow network.

MOTIVATION: The registration of serial section electron microscope images is a critical step in reconstructing biological tissue volumes, and it aims to eliminate complex nonlinear deformations from sectioning and replicate the correct neurite structure. However, due to the inherent properties of biological structures and the challenges posed by section preparation of biological tissues, achieving an accurate registration of serial sections remains a significant challenge. Conventional nonlinear registration techniques, which are effective in eliminating nonlinear deformation, can also eliminate the natural morphological variation of neurites across sections. Additionally, accumulation of registration errors alters the neurite structure. RESULTS: This article proposes a novel method for serial section registration that utilizes an unsupervised optical flow network to measure feature similarity rather than pixel similarity to eliminate nonlinear deformation and achieve pairwise registration between sections. The optical flow network is then employed to estimate and compensate for cumulative registration error, thereby allowing for the reconstruction of the structure of biological tissues. Based on the novel serial section registration method, a serial split technique is proposed for long-serial sections. Experimental results demonstrate that the state-of-the-art method proposed here effectively improves the spatial continuity of serial sections, leading to more accurate registration and improved reconstruction of the structure of biological tissues. AVAILABILITY AND IMPLEMENTATION: The source code and data are available at https://github.com/TongXin-CASIA/EFSR.

Recent progress in emergent two-dimensional silicene.

Although graphene is by far the most famous example of two-dimensional (2D) materials, which exhibits a wealth of exotic and intriguing properties, it suffers from a severe drawback. In this regard, the exploration of silicene, the silicon analog of the graphene material, has attracted substantial interest in the past decade. This review therefore provides a comprehensive survey of recent theoretical and experimental works on this 2D material. We first overview the distinctive structures and properties of silicene, including mechanical, electronic, and spintronic properties. We then discuss the growth and experimental characterization of silicene on Ag(111) and other different substrates, providing insights into the different phases or atomic arrangements of silicene observed on the metallic surfaces as well as on its electronic structures. Then, the recent state-of-the-art applications of silicene are summarized in section 4 with the aim to break the scientific and engineering barriers for application in nanoelectronics, sensors, energy storage devices, electrode materials, and quantum technology. Finally, the concluding remarks and the future prospects of silicene are also provided.

Accelerating drug repurposing for COVID-19 treatment by modeling mechanisms of action using cell image features and machine learning.

The novel coronavirus disease, COVID-19, has rapidly spread worldwide. Developing methods to identify the therapeutic activity of drugs based on phenotypic data can improve the efficiency of drug development. Here, a state-of-the-art machine-learning method was used to identify drug mechanism of actions (MoAs) based on the cell image features of 1105 drugs in the  LINCS database. As the multi-dimensional features of cell images are affected by non-experimental factors, the characteristics of similar drugs vary considerably, and it is difficult to effectively identify the MoA of drugs as there is substantial noise. By applying the supervised information theoretic metric-learning (ITML) algorithm, a linear transformation made drugs with the same MoA aggregate. By clustering drugs to communities and performing enrichment analysis, we found that transferred image features were more conducive to the recognition of drug MoAs. Image features analysis showed that different features play important roles in identifying different drug functions. Drugs that significantly affect cell survival or proliferation, such as cyclin-dependent kinase inhibitors, were more likely to be enriched in communities, whereas other drugs might be decentralized. Chloroquine and clomiphene, which block the entry of virus, were clustered into the same community, indicating that similar MoA could be reflected by the cell image. Overall, the findings of the present study laid the foundation for the discovery of MoAs of new drugs, based on image data. In addition, it provided a new method of drug repurposing for COVID-19. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-021-09727-5.

N-doped graphene for electrocatalytic O2 and CO2 reduction.

The electrocatalytic CO2 reduction reaction (CO2RR) and oxygen reduction reaction (ORR) are important approaches to realize energy conversion and sustainable development. However, sluggish reaction kinetics severely hinders the practical application of devices related to these reactions. N-doped graphene (NG) with unique properties exhibits great potential in catalyzing the CO2RR and ORR, which is attributed to the electron redistribution. In this review, we start from the fundamental properties of NG, especially emphasizing the changes caused by N doping. Then the synthetic methods are summarized by classifying them into top-down strategies and bottom-up strategies. Subsequently, the applications of NG in the ORR and CO2RR are discussed and the effects of electronic structure on the electrocatalytic activity are highlighted. Finally, we give our own perspective on the future research direction of NG in the applications of the ORR and CO2RR.

A new strategy for the fabrication of a flexible and highly sensitive capacitive pressure sensor.

The development of flexible capacitive pressure sensors has wide application prospects in the fields of electronic skin and intelligent wearable electronic devices, but it is still a great challenge to fabricate capacitive sensors with high sensitivity. Few reports have considered the use of interdigital electrode structures to improve the sensitivity of capacitive pressure sensors. In this work, a new strategy for the fabrication of a high-performance capacitive flexible pressure sensor based on MXene/polyvinylpyrrolidone (PVP) by an interdigital electrode is reported. By increasing the number of interdigital electrodes and selecting the appropriate dielectric layer, the sensitivity of the capacitive sensor can be improved. The capacitive sensor based on MXene/PVP here has a high sensitivity (~1.25 kPa-1), low detection limit (~0.6 Pa), wide sensing range (up to 294 kPa), fast response and recovery times (~30/15 ms) and mechanical stability of 10000 cycles. The presented sensor here can be used for various pressure detection applications, such as finger pressing, wrist pulse measuring, breathing, swallowing and speech recognition. This work provides a new method of using interdigital electrodes to fabricate a highly sensitive capacitive sensor with very promising application prospects in flexible sensors and wearable electronics.

Prediction of 2D ferromagnetism and monovalent europium ions in EuBr/graphene heterojunctions.

Europium, one of the rare-earth elements, exhibits +2 and +3 valence states and has been widely used for the magnetic modification of materials. Based on density functional theory calculations, we predicted 2D EuBr/graphene heterojunctions to exhibit metallicity, huge intrinsic-ferromagnetism nearly 7.0 µB per Eu and the special monovalent Eu ions. Electron localization function (ELF), difference charge densities and Bader charge analyses demonstrated that there are cation-π interactions between the EuBr films and graphene. Graphene works as a substrate to enable the stability of EuBr monolayer crystals, where EuBr plays an important role to yield ferromagnetism and enhance metallicity in the heterojunctions. Monte Carlo simulations were used to estimate a Curie temperature of about 7 K, which, together with magnetic configurations, can be further modulated by external strains and charge-carrier doping. In general, our theoretical work predicts the properties of novel 2D ferromagnetic EuBr/graphene heterojunctions, suggesting the possibility of combining 2D intrinsic-ferromagnetic metal halide crystals and graphene, and opening up a new perspective in next-generation electronic, spintronic devices and high-performance sensors.

Modeling drug mechanism of action with large scale gene-expression profiles using GPAR, an artificial intelligence platform.

BACKGROUND: Querying drug-induced gene expression profiles with machine learning method is an effective way for revealing drug mechanism of actions (MOAs), which is strongly supported by the growth of large scale and high-throughput gene expression databases. However, due to the lack of code-free and user friendly applications, it is not easy for biologists and pharmacologists to model MOAs with state-of-art deep learning approach. RESULTS: In this work, a newly developed online collaborative tool, Genetic profile-activity relationship (GPAR) was built to help modeling and predicting MOAs easily via deep learning. The users can use GPAR to customize their training sets to train self-defined MOA prediction models, to evaluate the model performances and to make further predictions automatically. Cross-validation tests show GPAR outperforms Gene set enrichment analysis in predicting MOAs. CONCLUSION: GPAR can serve as a better approach in MOAs prediction, which may facilitate researchers to generate more reliable MOA hypothesis.

Flexoelectricity Driven Fano Resonance in Slotted Carbon Nanotubes for Decoupled Multifunctional Sensing.

Multifunctionality, interference-free signal readout, and quantum effect are important considerations for flexible sensors equipped within a single unit towards further miniaturization. To address these criteria, we present the slotted carbon nanotube (CNT) junction features tunable Fano resonance driven by flexoelectricity, which could serve as an ideal multimodal sensory receptor. Based on extensive ab initio calculations, we find that the effective Fano factor can be used as a temperature-insensitive extrinsic variable for sensing the bending strain, and the Seebeck coefficient can be used as a strain-insensitive intrinsic variable for detecting temperature. Thus, this dual-parameter permits simultaneous sensing of temperature and strain without signal interference. We further demonstrate the applicability of this slotted junction to ultrasensitive chemical sensing which enables precise determination of donor-type, acceptor-type, and inert molecules. This is due to the enhancement or counterbalance between flexoelectric and chemical gating. Flexoelectric gating would preserve the electron-hole symmetry of the slotted junction whereas chemical gating would break it. As a proof-of-concept demonstration, the slotted CNT junction provides an excellent quantum platform for the development of multistimuli sensation in artificial intelligence at the molecular scale.

Structural tuning for enhanced magnetic performance by Y substitution in FeB-based metallic glasses.

Despite the compositional analogue to Fe71B17(NbYZr)12 metallic glass, the Fe71B17Y12 metallic glass has a saturated magnetization of Ca 108 emu g-1, more than 5 times of that in Fe71B17(NbYZr)12 (20 emu g-1). The structural origin for such significant difference in magnetic performance was investigated by x-ray absorption fine structure spectra and ab initio molecular dynamics (AIMD) simulations including simulated pair-correlation function (PCF) and Voronoi tessellation. Based on the Heisenberg model of magnetism, the narrow distribution of Fe-Fe bonds with larger distances accounts for a large Fe moment of 2.0 µ B in Fe71B17Y12, while the broad distribution of Fe-Fe bonds leads to ferrimagnetic couplings which result in the small net Fe moment of 0.45 µ B in Fe71B17(NbYZr)12. This work emphasizes how the substitution of analogous 4d transition metals induces a significantly different magnetism, which sheds lights on the development of new magnetic metallic glasses with both a promising magnetic performance and larger glass forming ability.

One Structure, Two Elements-LuGe2 Superconductor vs Ordinary Metallic Conductor LuSn2. A Case Study on How Site-Selective Germanium for Tin Atom Substitution Leads to Modulating of the Charge Distribution.

The substitution of chemically similar elements in a given crystal structure is an effective way to enhance physical properties, but the understanding on such improvements is usually impeded because the substitutions are random, and the roles of the different atoms cannot be distinguished by crystallographic symmetry. Herein, we provide a detailed crystallographic analysis and property measurements for the continuous solid solutions LuGexSn2-x (0 < x < 2). The results show that there is no apparent change of the global symmetry, with the end-members LuGe2 and LuSn2, as well as the intermediate LuGexSn2-x compositions adopting the ZrSi2 type structure (space group Cmcm, Pearson index oC12). Yet, the refinements of the crystal structures from single-crystal X-ray diffraction data show that Ge-Sn atom substitutions are not random, but occur preferentially at the zigzag chain. The patterned distribution of two group 14 elements leads to a significant variation in chemical bonding and charge ordering within the other structural fragment, the 2D square nets, thereby resulting in tuned electron transport. The enhancement is greater than that for the typical Bloch-Gruneisen model and more akin to that for the parallel-resistor model. Magnetization measurements on single crystals show bulk superconductivity in all LuGexSn2-x samples with shielding fractions as high as 90%. Specific heat data confirm the effect to originate from residual metallic tin in the material, indicating that Sn atom substitutions in the 2D square nets cause disruptions of the hypervalent bonding and local anisotropy, which ultimately leads to vanishing of the superconducting state in the end-member LuGe2. This work sheds light on how the complexity in chemical interactions by two different carbon congeners leads to changes in the physical properties and how they can be correlated with the induced charge distribution. These studies also provide a general approach to modulation of charge density and. thus, of emerging physical properties in other classes of intermetallic systems based on the main-group elements of groups 13 to 15.

A highly sensitive piezoresistive sensor based on MXenes and polyvinyl butyral with a wide detection limit and low power consumption.

As a new class of two-dimensional transition-metal carbides and carbonitrides, MXenes have been widely used in energy storage, sensing, catalysis, electromagnetic interference shielding and other fields. It is a challenge to simultaneously realize a sensor with extremely high sensitivity, wide detection limits, low power consumption and good mechanical stability. In this work, taking advantage of the high conductivity of MXenes and the porous structure of polyvinyl butyral, a highly sensitive piezoresistive sensor was fabricated. The fabricated MXene/PVB-based sensor exhibits high sensitivity and reliability with a factor of ∼11.9 kPa-1, ∼1.15 kPa-1 and ∼0.20 kPa-1 in the ranges of 31.2 Pa-312 Pa, 312 Pa-62.4 kPa and 62.4 kPa-1248.4 kPa, respectively. The sensor has a wide detection range (∼31.2 Pa to ∼2.205 MPa), low detection limit (6.8 Pa), low detection voltage (0.1 mV), low power consumption (∼3.6 × 10-10 W), fast response time (∼110 ms) and good mechanical stability (over 10 000 maximum-pressure cycles). Moreover, it is demonstrated that the sensor can detect subtle bending and release activities of humans, including arterial pulses and voice signals, which makes it potentially suitable to be used as a wide detection range, highly sensitive and low power consumption piezoresistive sensor. This work provides a new avenue to expand the application of MXene-based flexible pressure sensors with a wide sensing range and ultra-low power consumption.

Nickel-metal-organic framework nanobelt based composite membranes for efficient Sr2+ removal from aqueous solution.

The sorption removal of radionuclides Sr2+ using a freestanding functional membrane is an interesting and significant research area in the remediation of radioactive wastes. Herein, a novel self-assembled membrane consisting of metal-organic framework (MOF) nanobelts and graphene oxides (GOs) are synthesized through a simple and facile filtration method. The membrane possesses a unique interwove morphology as evidenced from SEM images. Batch experiments suggest that the GO/Ni-MOF composite membrane could remove Sr2+ ions from aqueous solutions and the Sr2+ adsorption capacity and efficiency of the GO/Ni-MOF composite membrane is relevant to the MOF content in the composite. Thus, the dominant interaction mechanism was interface or surface complexation, electrostatic interaction as well as ion substitution. The maximum effective sorption of Sr2+ over GO/Ni-MOF membrane is 32.99% with 2 mg composite membrane containing a high content of Ni-MOF at 299 K in 100 mg/L Sr2+ aqueous solution. The FT-IR and XPS results suggest that the synergistic effect between GO and Ni-MOF is determinant in the sorption Sr2+ process. The GO/Ni-MOF composite membrane is demonstrated to have the advantages of efficient removal of Sr2+, low cost and simple synthesis route, which is promising in the elimination of radionuclide contamination.

AI-Enabled Wearable and Flexible Electronics for Assessing Full Personal Exposures.

Research on the exposome has been extended to personal exposures, and full assessment of personal exposures is of great significance for personal health monitoring and epidemiological studies. Compared with static measurement instruments, wearable sensors are more suitable for dynamic personal exposures assessment. The development of flexible wearable sensors with the features of being physically comfortable and easy to use can be a promising solution for the measurement of personal exposures. With the support of big data and AI, large-scale personal exposures assessment could foster the transition from population-based to individual-based epidemiological studies and upgrade the intelligence level of medical services.

Structural analysis of Gd6FeBi2 from single-crystal X-ray diffraction methods and electronic structure calculations.

The crystal structure of the gadolinium iron bismuthide Gd6FeBi2 has been characterized by single-crystal X-ray diffraction data and analyzed in detail using first-principles calculations. The structure is isotypic with the Zr6CoAl2 structure, which is a variant of the ZrNiAl structure and its binary prototype Fe2P (Pearson code hP9, Wyckoff sequence g f d a). As such, the structure is best viewed as an array of tricapped trigonal prisms of Gd atoms centered alternately by Fe and Bi. The magnetic-ordering temperature of this compound (ca 350 K) is much higher than that of other rare-earth metal-rich phases with the same or related structures. It is also higher than the ordering temperature of many other Gd-rich ternary phases, where the magnetic exchange is typically governed by Ruderman-Kittel-Kasuya-Yosida (RKKY) interactions. First-principles calculations reveal a larger than expected Gd magnetic moment, with the additional contribution arising from the Gd 5d electrons. The electronic structure analysis suggests strong Gd 5d-Fe 3d hybridization to be the cause of this effect, rather than weak interactions between Gd and Bi. These details are of importance for understanding the magnetic response and explaining the high ordering temperature in this material.

Plasmonic Light Illumination Creates a Channel To Achieve Fast Degradation of Ti3C2T x Nanosheets.

Two-dimensional (2D) material-controllable degradation under light radiation is crucial for their photonics and medical-related applications, which are yet to be investigated. In this paper, we first report the laser illumination method to regulate the degradation rate of Ti3C2T x nanosheets in aqueous solution. Comprehensive characterization of intermediates and final products confirmed that plasmonic laser promoting the oxidation was strikingly different from heating the aqueous solution homogeneously. Laser illumination would nearly 10 times accelerate the degradation of Ti3C2T x nanosheets in initial stage and create many smaller-sized oxidized products in a short time. Laser-induced fast degradation was principally ascribed to surface plasmonic resonance effect of Ti3C2T x nanosheets. The degradation ability of such illumination could be controlled either by tuning the excitation wavelength or changing the excitation power. Furthermore, the laser- or thermal-induced degradation could be retarded by surface protection of Ti3C2T x nanosheets. Our results suggest that plasmonic electron excitation of Ti3C2T x nanosheets could build a new reaction channel and lead to the fast oxidation of nanosheets in aqueous solution, potentially enabling a series of water-based applications.

Casting amorphorized SnO2/MoO3 hybrid into foam-like carbon nanoflakes towards high-performance pseudocapacitive lithium storage.

We report an amorphorization-hybridization strategy to enhance lithium storage by casting atomically mixed amorphorized SnO2/MoO3 into porous foam-like carbon nanoflakes (denote as SnO2/MoO3@CNFs, or SMC in short), which are simply prepared by annealing tin(II)/molybdenum(IV) 2-ethylhexanoate within CNFs under ambient atmosphere at a low temperature (300 °C). The SnO2/MoO3 loading amount within CNFs can be easily adjusted by controlling the Sn/Mo/C precursors. When examined as lithium ion battery (LIB) anode materials, the amorphorized SnO2/MoO3@CNFs with carbon content of 32 wt% (also denote as SMC-32, in which the number represents the carbon content) deliver a high reversible capacity of 1120.5 mA h/g after 200 cycles at 200 mA/g and then 651.5 mA h/g after another 300 cycles at 2000 mA/g, which is much better than that of the crystalline SnO2/CNFs (carbon content of 34 wt%), MoO3/CNFs (carbon content of 22.7 wt%), or SnO2/MoO3@CNFs (with lower carbon contents of 11 and 25 wt%). The electrochemical measurements as well as the ex situ structure characterization clearly suggest that combination of amorphorization and hybridization of SnO2/MoO3 with CNFs synergistically contributes to the superior lithium storage performance with high pseudocapacitive contribution.

High-performance asymmetric micro-supercapacitors based on electrodeposited MnO2 and N-doped graphene.

In-plane asymmetric micro-supercapacitors using nitrogen-doped graphene (NG) film as negative electrode and MnO2 nanostructures as positive electrode are fabricated onto a plastic substrate coated with Ni/Cu film. A laser-scribing machine is employed to make interdigital finger electrodes in the plastic substrate coated with NG film via a slurry coating process. MnO2 nanosheets are electrochemically deposited onto pre-coated NG film. In LiCl-based gelled electrolyte, the NG//MnO2 cell exhibits excellent electrochemical performance and a broad voltage window up to 1.8 V. The maximum specific capacitance of a single cell is measured to be 13 mF cm-2. In addition, several cells in series can be easily fabricated by combining the laser-scribing technique and the electrodeposition of MnO2 electrodes. As a proof of concept, four cells in a compact configuration and with high voltage output up to 7.2 V are demonstrated.