Bismuth-doping boosting Na+ diffusion kinetics of layered oxide cathode with radially oriented {010} active lattice facet for sodium-ion batteries.

O3-type layered oxide cathodes (NaxTMO2) for sodium-ion batteries (SIBs) have attracted significant attention as one of the most promising potential candidates for practical energy storage applications. The poor Na+ diffusion kinetics is, however, one of the major obstacles to advancing large-scale practical application. Herein, we report bismuth-doped O3-NaNi0.5Mn0.5O2 (NMB) microspheres consisting of unique primary nanoplatelets with the radially oriented {010} active lattice facets. The NMB combines the advantages of the oriented and exposed electrochemical active planes for direct paths of Na+ diffusion, and the thick primary nanoplatelets for less surface parasitic reactions with the electrolyte. Consequently, the NMB cathode exhibits a long-term stability with an excellent capacity retention of 72.5% at 1C after 300 cycles and an enhanced rate capability at a 0.1C to 10C rate (1C = 240 mA g-1). Furthermore, the enhancement is elucidated by the small volume change, thin cathode-electrolyte-interphase (CEI) layer, and rapid Na+ diffusion kinetics. In particular, the radial orientation-based Bi-doping strategy is demonstrated to be effective at boosting electrochemical performance in other layered oxides (such as Bi-doped NaNi0.45Mn0.45Ti0.1O2 and NaNi1/3Fe1/3Mn1/3O2). The results provide a promising strategy of utilizing the advantages of the oriented active facets of primary platelets and secondary particles to develop high-rate layered oxide cathodes for SIBs.

A Reconfigurable Near-Sensor Processor for Anomaly Detection in Limb Prostheses.

This paper presents a reconfigurable near-sensor anomaly detection processor to real-time monitor the potential anomalous behaviors of amputees with limb prostheses. The processor is low-power, low-latency, and suitable for equipment on the prostheses and comprises a reconfigurable Variational Autoencoder (VAE), a scalable Self-Organizing Map (SOM) Array, and a window-size-adjustable Markov Chain, which can implement an integrated miniaturized anomaly detection system. With the reconfigurable VAE, the proposed processor can support up to 64 sensor sampling channels programmable by global configuration, which can meet the anomaly detection requirements in different scenarios. A scalable SOM array allows for the selection of different sizes based on the complexity of the data. Unlike traditional time accumulation-based anomaly detection methods, the Markov Chain is utilized to detect time-series-based anomalous data. The processor is designed and fabricated in a UMC 40-nm LP technology with a core area of 1.49 mm2 and a power consumption of 1.81 mW. It achieves real-time detection performance with 0.933 average F1 Score for the FSP dataset within 24.22 µs, and 0.956 average F1 Score for the SFDLA-12 dataset within 30.48 µs, respectively. The energy dissipation of detection for each input feature is 43.84 nJ with the FSP dataset, and 55.17 nJ with the SFDLA-12 dataset. Compared with ARM Cortex-M4 and ARM Cortex-M33 microcontrollers, the processor achieves energy and area efficiency improvements ranging from 257×, 193× and 11×, 8×, respectively.

Atomically Dispersed Iron Regulating Electronic Structure of Iron Atom Clusters for Electrocatalytic H2 O2 Production and Biomass Upgrading.

The integration of highly active single atoms (SAs) and atom clusters (ACs) into an electrocatalyst is critically important for high-efficiency two-electron oxygen reduction reaction (2e- ORR) to hydrogen peroxide (H2 O2 ). Here we report a tandem impregnation-pyrolysis-etching strategy to fabricate the oxygen-coordinated Fe SAs and ACs anchored on bacterial cellulose-derived carbon (BCC) (FeSAs/ACs-BCC). As the electrocatalyst, FeSAs/ACs-BCC exhibits superior electrocatalytic activity and selectivity toward 2e- ORR, affording an onset potential of 0.78 V (vs. RHE) and a high H2 O2 selectivity of 96.5 % in 0.1 M KOH. In a flow cell reactor, the FeSAs/ACs-BCC also achieves high-efficiency H2 O2 production with a yield rate of 12.51±0.18 mol gcat -1 h-1 and a faradaic efficiency of 89.4 %±1.3 % at 150 mA cm-2 . Additionally, the feasibility of coupling the produced H2 O2 and electro-Fenton process for the valorization of ethylene glycol was explored in detail. The theoretical calculations uncover that the oxygen-coordinated Fe SAs effectively regulate the electronic structure of Fe ACs which are the 2e- ORR active sites, resulting in the optimal binding strength of *OOH intermediate for high-efficiency H2 O2 production.

A Memristor-Based Learning Engine for Synaptic Trace-Based Online Learning.

The memristor has been extensively used to facilitate the synaptic online learning of brain-inspired spiking neural networks (SNNs). However, the current memristor-based work can not support the widely used yet sophisticated trace-based learning rules, including the trace-based Spike-Timing-Dependent Plasticity (STDP) and the Bayesian Confidence Propagation Neural Network (BCPNN) learning rules. This paper proposes a learning engine to implement trace-based online learning, consisting of memristor-based blocks and analog computing blocks. The memristor is used to mimic the synaptic trace dynamics by exploiting the nonlinear physical property of the device. The analog computing blocks are used for the addition, multiplication, logarithmic and integral operations. By organizing these building blocks, a reconfigurable learning engine is architected and realized to simulate the STDP and BCPNN online learning rules, using memristors and 180 nm analog CMOS technology. The results show that the proposed learning engine can achieve energy consumption of 10.61 pJ and 51.49 pJ per synaptic update for the STDP and BCPNN learning rules, respectively, with a 147.03× and 93.61× reduction compared to the 180 nm ASIC counterparts, and also a 9.39× and 5.63× reduction compared to the 40 nm ASIC counterparts. Compared with the state-of-the-art work of Loihi and eBrainII, the learning engine can reduce the energy per synaptic update by 11.31× and 13.13× for trace-based STDP and BCPNN learning rules, respectively.

In-situ constructed Cu/CuNC interfaces for low-overpotential reduction of CO2 to ethanol.

Electrochemical CO2 reduction (ECR) to high-value multi-carbon (C2+) products is critical to sustainable energy conversion, yet the high energy barrier of C-C coupling causes catalysts to suffer high overpotential and low selectivity toward specific liquid C2+ products. Here, the electronically asymmetric Cu-Cu/Cu-N-C (Cu/CuNC) interface site is found, by theoretical calculations, to enhance the adsorption of *CO intermediates and decrease the reaction barrier of C-C coupling in ECR, enabling efficient C-C coupling at low overpotential. The catalyst consisting of high-density Cu/CuNC interface sites (noted as ER-Cu/CuNC) is then accordingly designed and constructed in situ on the high-loading Cu-N-C single atomic catalysts. Systematical experiments corroborate the theoretical prediction that the ER-Cu/CuNC boosts electrocatalytic CO2-to-ethanol conversion with a Faradaic efficiency toward C2+ of 60.3% (FEethanol of 55%) at a low overpotential of -0.35 V. These findings provide new insights and an attractive approach to creating electronically asymmetric dual sites for efficient conversion of CO2 to C2+ products.

Interfacial assembly of binary atomic metal-Nx sites for high-performance energy devices.

Anion-exchange membrane fuel cells and Zn-air batteries based on non-Pt group metal catalysts typically suffer from sluggish cathodic oxygen reduction. Designing advanced catalyst architectures to improve the catalyst's oxygen reduction activity and boosting the accessible site density by increasing metal loading and site utilization are potential ways to achieve high device performances. Herein, we report an interfacial assembly strategy to achieve binary single-atomic Fe/Co-Nx with high mass loadings through constructing a nanocage structure and concentrating high-density accessible binary single-atomic Fe/Co-Nx sites in a porous shell. The prepared FeCo-NCH features metal loading with a single-atomic distribution as high as 7.9 wt% and an accessible site density of around 7.6 × 1019 sites g-1, surpassing most reported M-Nx catalysts. In anion exchange membrane fuel cells and zinc-air batteries, the FeCo-NCH material delivers peak power densities of 569.0 or 414.5 mW cm-2, 3.4 or 2.8 times higher than control devices assembled with FeCo-NC. These results suggest that the present strategy for promoting catalytic site utilization offers new possibilities for exploring efficient low-cost electrocatalysts to boost the performance of various energy devices.

Identification of the active triple-phase boundary of a non-Pt catalyst layer in fuel cells.

The rational design of non-Pt oxygen reduction reaction (ORR) catalysts and catalyst layers in fuel cells is largely impeded by insufficient knowledge of triple-phase boundaries (TPBs) in the micropore and mesopore ranges. Here, we developed a size-sensitive molecular probe method to resolve the TPB of Fe/N/C catalyst layers in these size ranges. More than 70% of the ORR activity was found to be contributed by the 0.8- to 2.0-nanometer micropores of Fe/N/C catalysts, even at a low micropore area fraction of 29%. Acid-alkaline interactions at the catalyst-polyelectrolyte interface deactivate the active sites in mesopores and macropores, resulting in inactive TPBs, leaving micropores without the interaction as the active TPBs. The concept of active and inactive TPBs provides a previously unidentified design principle for non-Pt catalyst and catalyst layers in fuel cells.

Buffering the local pH via single-atomic Mn-N auxiliary sites to boost CO2 electroreduction.

Electrocatalytic CO2 reduction driven by renewable energy has become a promising approach to rebalance the carbon cycle. Atomically dispersed transition metals anchored on N-doped carbon supports (M-N-C) have been considered as the most attractive catalysts to catalyze CO2 to CO. However, the sluggish kinetics of M-N-C limits the large-scale application of this type of catalyst. Here, it is found that the introduction of single atomic Mn-N auxiliary sites could effectively buffer the locally generated OH- on the catalytic interface of the single-atomic Ni-N-C sites, thus accelerating proton-coupled electron transfer (PCET) steps to enhance the CO2 electroreduction to CO. The constructed diatomic Ni/Mn-N-C catalysts show a CO faradaic efficiency of 96.6% and partial CO current density of 13.3 mA cm-2 at -0.76 V vs. RHE, outperforming that of monometallic single-atomic Ni-N-C or Mn-N-C counterparts. The results suggest that constructing synergistic catalytic sites to regulate the surface local microenvironment might be an attractive strategy for boosting CO2 electroreduction to value-added products.

AQDS Activates Extracellular Synergistic Biodetoxification of Copper and Selenite via Altering the Coordination Environment of Outer-Membrane Proteins.

The biotransformation of heavy metals in the environment is usually affected by co-existing pollutants like selenium (Se), which may lower the ecotoxicity of heavy metals, but the underlying mechanisms remain unclear. Here, we shed light on the pathways of copper (Cu2+) and selenite (SeO32-) synergistic biodetoxification by Shewanella oneidensis MR-1 and illustrate how such processes are affected by anthraquinone-2,6-disulfonate (AQDS), an analogue of humic substances. We observed the formation of copper selenide nanoparticles (Cu2-xSe) from synergistic detoxification of Cu2+ and SeO32- in the periplasm. Interestingly, adding AQDS triggered a fundamental transition from periplasmic to extracellular reaction, enabling 14.7-fold faster Cu2+ biodetoxification (via mediated electron transfer) and 11.4-fold faster SeO32- detoxification (via direct electron transfer). This is mainly attributed to the slightly raised redox potential of the heme center of AQDS-coordinated outer-membrane proteins that accelerates electron efflux from the cells. Our work offers a fundamental understanding of the synergistic detoxification of heavy metals and Se in a complicated environmental matrix and unveils an unexpected role of AQDS beyond electron mediation, which may guide the development of more efficient environmental remediation and resource recovery biotechnologies.

Suppressing Electron Back-Donation for a Highly CO-tolerant Fuel Cell Anode Catalyst via Cobalt Modulation.

Platinum on carbon (Pt/C) catalyst is commercially adopted in fuel cells but it undergoes formidable active-site poisoning by carbon monoxide (CO). In particular, given the sluggish kinetics of hydrogen oxidation reaction (HOR) in anion-exchange membrane fuel cell (AEMFC), the issues of Pt poisoning and slow rate would combine mutually, notably worsening the device performances. Here we overcome these challenges through incorporating cobalt (Co) into molybdenum-nickel alloy (MoNi4 ), termed Co-MoNi4 , which not only shows superior HOR activity over the Pt/C catalyst in alkali, but more intriguingly exhibits excellent CO tolerance with only small activity decay after 10 000 cycles in the presence of 500 parts per million (ppm) CO. When feeding with CO (250 ppm)/H2 , the AEMFC assembled by this catalyst yields a peak power density of 394 mW cm-2 , far exceeding the Pt/C catalyst. Experimental and computational studies reveal that weakened CO chemisorption originates from the electron-deficient Ni sites after Co incorporation that suppresses d→CO 2π* back-donation.

Multi-slice spiral CT findings of tubulovillous adenoma of the duodenum.

OBJECTIVES: To analyze the appearance of duodenal tubulovillous adenoma on multi-slice spiral CT images to facilitate early diagnosis and treatment to potentially improve prognosis. METHODS: We retrospectively analyzed clinical data and CT imaging findings of 11 cases of duodenal tubulovillous adenomas, all confirmed by pathology. The location, size, shape, CT density, relationship with surrounding structures, accompanying bile duct obstruction, and enhancement pattern of each lesion were documented. RESULTS: All 11 lesions occurred in the descending part of the duodenum. Ten cases occurred in the duodenal papilla area. Nine cases had a low-density ring sign or semicircle sign between the lesion and the adjacent normal intestinal wall on axial images. Eight cases had differing degrees of bile duct dilatation, five of which had concomitant pancreatic duct dilatation. Noncontrast images revealed uniform soft tissue density; contrast enhanced images showed moderate, mostly uniform enhancement, with the most enhancement in the venous phase. In the arterial phase, two lesions showed linear enhancing vessels. CONCLUSIONS: On multi-slice spiral CT imaging, duodenal tubulovillous adenomas have certain characteristics that could be used for clinical diagnosis and treatment. PRECIS: On multi-slice spiral CT imaging of duodenal tubulovillous adenoma, findings of nodular or cauliflower-like shape, uniform density, uniform moderate enhancement, and a peripheral low-density ring sign could improve diagnostic accuracy.

Fabricating polyoxometalates-stabilized single-atom site catalysts in confined space with enhanced activity for alkynes diboration.

Effecting the synergistic function of single metal atom sites and their supports is of great importance to achieve high-performance catalysts. Herein, we successfully fabricate polyoxometalates (POMs)-stabilized atomically dispersed platinum sites by employing three-dimensional metal-organic frameworks (MOFs) as the finite spatial skeleton to govern the accessible quantity, spatial dispersion, and mobility of metal precursors around each POM unit. The isolated single platinum atoms (Pt1) are steadily anchored in the square-planar sites on the surface of monodispersed Keggin-type phosphomolybdic acid (PMo) in the cavities of various MOFs, including MIL-101, HKUST-1, and ZIF-67. In contrast, either the absence of POMs or MOFs yielded only platinum nanoparticles. Pt1-PMo@MIL-101 are seven times more active than the corresponding nanoparticles in the diboration of phenylacetylene, which can be attributed to the synergistic effect of the preconcentration of organic reaction substrates by porous MOFs skeleton and the decreased desorption energy of products on isolated Pt atom sites.

Ternary nickel-tungsten-copper alloy rivals platinum for catalyzing alkaline hydrogen oxidation.

Operating fuel cells in alkaline environments permits the use of platinum-group-metal-free (PGM-free) catalysts and inexpensive bipolar plates, leading to significant cost reduction. Of the PGM-free catalysts explored, however, only a few nickel-based materials are active for catalyzing the hydrogen oxidation reaction (HOR) in alkali; moreover, these catalysts deactivate rapidly at high anode potentials owing to nickel hydroxide formation. Here we describe that a nickel-tungsten-copper (Ni5.2WCu2.2) ternary alloy showing HOR activity rivals Pt/C benchmark in alkaline electrolyte. Importantly, we achieved a high anode potential up to 0.3 V versus reversible hydrogen electrode on this catalyst with good operational stability over 20 h. The catalyst also displays excellent CO-tolerant ability that Pt/C catalyst lacks. Experimental and theoretical studies uncover that nickel, tungsten, and copper play in synergy to create a favorable alloying surface for optimized hydrogen and hydroxyl bindings, as well as for the improved oxidation resistance, which result in the HOR enhancement.

Interface-Promoted Direct Oxidation of p-Arsanilic Acid and Removal of Total Arsenic by the Coupling of Peroxymonosulfate and Mn-Fe-Mixed Oxide.

As one of the extensively used feed additives in livestock and poultry breeding, p-arsanilic acid (p-ASA) has become an organoarsenic pollutant with great concern. For the efficient removal of p-ASA from water, the combination of chemical oxidation and adsorption is recognized as a promising process. Herein, hollow/porous Mn-Fe-mixed oxide (MnFeO) nanocubes were synthesized and used in coupling with peroxymonosulfate (PMS) to oxidize p-ASA and remove the total arsenic (As). Under acidic conditions, both p-ASA and total As could be completely removed in the PMS/MnFeO process and the overall performance was substantially better than that of the Mn/Fe monometallic system. More importantly, an interface-promoted direct oxidation mechanism was found in the p-ASA-involved PMS/MnFeO system. Rather than activate PMS to generate reactive oxygen species (i.e., SO4·-, ·OH, and 1O2), the MnFeO nanocubes first adsorbed p-ASA to form a ligand-oxide interface, which improved the oxidation of the adsorbed p-ASA by PMS and ultimately enhanced the removal of the total As. Such a direct oxidation process achieved selective oxidation of p-ASA and avoidance of severe interference from the commonly present constituents in real water samples. After facile elution with dilute alkali solution, the used MnFeO nanocubes exhibited superior recyclability in the repeated p-ASA removal experiments. Therefore, this work provides a promising approach for efficient abatement of phenylarsenical-caused water pollution based on the PMS/MnFeO oxidation process.

Grey hematite photoanodes decrease the onset potential in photoelectrochemical water oxidation.

Photoelectrochemical (PEC) water splitting for solar energy conversion into chemical fuels has attracted intense research attention. The semiconductor hematite (α-Fe2O3), with its earth abundance, chemical stability, and efficient light harvesting, stands out as a promising photoanode material. Unfortunately, its electron affinity is too deep for overall water splitting, requiring additional bias. Interface engineering has been used to reduce the onset potential of hematite photoelectrode. Here we focus instead on energy band engineering hematite by shrinking the crystal lattice, and the water-splitting onset potential can be decreased from 1.14 to 0.61 V vs. the reversible hydrogen electrode. It is the lowest record reported for a pristine hematite photoanode without surface modification. X-ray absorption spectroscopy and magnetic properties suggest the redistribution of 3d electrons in the as-synthesized grey hematite electrode. Density function theory studies herein show that the smaller-lattice-constant hematite benefits from raised energy bands, which accounts for the reduced onset potential.

[Characteristics, Sources, and Health Risks of Elements in PM2.5 in Shanxi University Town].

In order to investigate the pollution characteristics and sources of elements in PM2.5 in the Shanxi University Town in 2017, an energy dispersive X-ray fluorescence spectrometer (ED-XRF) was used to analyze 21 kinds of elements in PM2.5 samples. A health risk assessment was conducted for Mn, Zn, Cu, Sb, Pb, Cr, Co, and Ni. The main sources of elements were identified by the principal component analysis (PCA) and positive matrix factorization (PMF). The results found that, among the 21 kinds of elements in PM2.5 in Shanxi University Town, the mass concentration of Ca was the highest, followed by Si, Fe, Al, S, K, and Cl. These seven elements accounted for 95.71% of the total element concentrations. The concentration of Cr exceeded the annual average concentration limit of ambient air quality standards in China by 104 times. The concentration of Ca in PM2.5 was the highest in spring, summer, and winter, while in autumn the concentration of S was the highest. Mn was the element that had non-carcinogenic risks to the three population types, and the level of risks were in the order of children > adult men > adult women. Cr and Co had tolerable carcinogenic risks, and the risk levels were in the order of adult men > adult women > children. The main sources of elements in PM2.5 in Shanxi University Town in 2017 were natural mineral dust, urban dust, coal combustion, and traffic.

Bimetallic nickel-molybdenum/tungsten nanoalloys for high-efficiency hydrogen oxidation catalysis in alkaline electrolytes.

Hydroxide exchange membrane fuel cells offer possibility of adopting platinum-group-metal-free catalysts to negotiate sluggish oxygen reduction reaction. Unfortunately, the ultrafast hydrogen oxidation reaction (HOR) on platinum decreases at least two orders of magnitude by switching the electrolytes from acid to base, causing high platinum-group-metal loadings. Here we show that a nickel-molybdenum nanoalloy with tetragonal MoNi4 phase can catalyze the HOR efficiently in alkaline electrolytes. The catalyst exhibits a high apparent exchange current density of 3.41 milliamperes per square centimeter and operates very stable, which is 1.4 times higher than that of state-of-the-art Pt/C catalyst. With this catalyst, we further demonstrate the capability to tolerate carbon monoxide poisoning. Marked HOR activity was also observed on similarly designed WNi4 catalyst. We attribute this remarkable HOR reactivity to an alloy effect that enables optimum adsorption of hydrogen on nickel and hydroxyl on molybdenum (tungsten), which synergistically promotes the Volmer reaction.

Electrocatalytically Active Fe-(O-C2 )4 Single-Atom Sites for Efficient Reduction of Nitrogen to Ammonia.

Single-atom catalysts have demonstrated their superiority over other types of catalysts for various reactions. However, the reported nitrogen reduction reaction single-atom electrocatalysts for the nitrogen reduction reaction exclusively utilize metal-nitrogen or metal-carbon coordination configurations as catalytic active sites. Here, we report a Fe single-atom electrocatalyst supported on low-cost, nitrogen-free lignocellulose-derived carbon. The extended X-ray absorption fine structure spectra confirm that Fe atoms are anchored to the support via the Fe-(O-C2 )4 coordination configuration. Density functional theory calculations identify Fe-(O-C2 )4 as the active site for the nitrogen reduction reaction. An electrode consisting of the electrocatalyst loaded on carbon cloth can afford a NH3 yield rate and faradaic efficiency of 32.1 µg h-1 mgcat. -1 (5350 µg h-1 mgFe -1 ) and 29.3 %, respectively. An exceptional NH3 yield rate of 307.7 µg h-1 mgcat. -1 (51 283 µg h-1 mgFe -1 ) with a near record faradaic efficiency of 51.0 % can be achieved with the electrocatalyst immobilized on a glassy carbon electrode.

Rational Construction of Porous Metal-Organic Frameworks for Uranium(VI) Extraction: The Strong Periodic Tendency with a Metal Node.

Although metal-organic frameworks (MOFs) have been reported as important porous materials for the potential utility in metal ion separation, coordinating the functionality, structure, and component of MOFs remains a great challenge. Herein, a series of anionic rare earth MOFs (RE-MOFs) were synthesized via a solvothermal template reaction and for the first time explored for uranium(VI) capture from an acidic medium. The unusually high extraction capacity of UO22+ (e.g., 538 mg U per g of Y-MOF) was achieved through ion-exchange with the concomitant release of Me2NH2+, during which the uranium(VI) extraction in the series of isostructural RE-MOFs was found to be highly sensitive to the ionic radii of the metal nodes. That is, the uranium(VI) adsorption capacities continuously increased as the ionic radii decreased. In-depth mechanism insight was obtained from molecular dynamics simulations, suggesting that both the accessible pore volume of the MOFs and hydrogen-bonding interactions contribute to the strong periodic tendency of uranium(VI) extraction.

A Smart Dental Health-IoT Platform Based on Intelligent Hardware, Deep Learning, and Mobile Terminal.

The dental disease is a common disease for a human. Screening and visual diagnosis that are currently performed in clinics possibly cost a lot in various manners. Along with the progress of the Internet of Things (IoT) and artificial intelligence, the internet-based intelligent system have shown great potential in applying home-based healthcare. Therefore, a smart dental health-IoT system based on intelligent hardware, deep learning, and mobile terminal is proposed in this paper, aiming at exploring the feasibility of its application on in-home dental healthcare. Moreover, a smart dental device is designed and developed in this study to perform the image acquisition of teeth. Based on the data set of 12 600 clinical images collected by the proposed device from 10 private dental clinics, an automatic diagnosis model trained by MASK R-CNN is developed for the detection and classification of 7 different dental diseases including decayed tooth, dental plaque, uorosis, and periodontal disease, with the diagnosis accuracy of them reaching up to 90%, along with high sensitivity and high specificity. Following the one-month test in ten clinics, compared with that last month when the platform was not used, the mean diagnosis time reduces by 37.5% for each patient, helping explain the increase in the number of treated patients by 18.4%. Furthermore, application software (APPs) on mobile terminal for client side and for dentist side are implemented to provide service of pre-examination, consultation, appointment, and evaluation.