科研成果

The cycling of iron at the Earth’s near surface is profoundly influenced by dissimilatory metal reducing microorganisms, and many studies have focused on unraveling electron transfer mechanisms between these bacteria and Fe(III)-(oxyhydr)oxides. However, these efforts have been complicated by the fact that these minerals often occur in the micro- to nanosize regime, and in relevant natural environments as well as in the laboratory are subject to aggregation. The nature of the physical interface between the cellular envelope, the outer-membrane cytochromesresponsible for facilitating the interfacial electron transfer step, and these complex mineral particulates is thus difficult to probe. Previous studies using whole cells have reported reduction rates that do not correlate with particle size. In the present study we isolate the interaction between the decaheme outer-membrane cytochrome OmcA of Shewanella oneidensisand nanoparticulate hematite, examining the reduction rate as a function of particle size and reaction products through detailed characterization of the electron balance and the structure and valence of iron at particle surfaces. By comparison with abiotic reduction via the smaller molecule ascorbic acid, we show that the reduction rate is systematically controlled by the sterically accessible interfacial contact area between OmcA and hematite in particle aggregates; rates increase once pore throat sizes in aggregates become as large as OmcA. Simultaneous measure of OmcA oxidation against Fe(II) release shows a ratio of 1:10, consistent with a cascade OmcA oxidation mechanism heme by heme. X-ray absorption spectroscopies reveal incipient magnetite on the reacted surfaces of the hematite nanoparticles after reaction. The collective findings establish the importance of accessibility of physical contact between the terminal reductases and iron oxide surfaces, and through apparent consistency of observations help reconcile behavior reported at the larger more complex scale of whole cell studies.

Visual perceptual learning models, as constrained by orientation and location specificities, propose that learning either reflects changes in V1 neuronal tuning or reweighting specific V1 inputs in either the visual cortex or higher areas. Here we demonstrate that, with a training-plus-exposure procedure, in which observers are trained at one orientation and either simultaneously or subsequently passively exposed to a second transfer orientation, perceptual learning can completely transfer to the second orientation in tasks known to be orientation-specific. However, transfer fails if exposure precedes the training. These results challenge the existing specific perceptual learning models by suggesting a more general perceptual learning process. We propose a rule-based learning model to explain perceptual learning and its specificity and transfer. In this model, a decision unit in high-level brain areas learns the rules of reweighting the V1 inputs through training. However, these rules cannot be applied to a new orientation/location because the decision unit cannot functionally connect to the new V1 inputs that are unattended or even suppressed after training at a different orientation/location, which leads to specificity. Repeated orientation exposure or location training reactivates these inputs to establish the functional connections and enable the transfer of learning.

Visual perceptual learning models, as constrained by orientation and location specificities, propose that learning either reflects changes in V1 neuronal tuning or reweighting specific V1 inputs in either the visual cortex or higher areas. Here we demonstrate that, with a training-plus-exposure procedure, in which observers are trained at one orientation and either simultaneously or subsequently passively exposed to a second transfer orientation, perceptual learning can completely transfer to the second orientation in tasks known to be orientation-specific. However, transfer fails if exposure precedes the training. These results challenge the existing specific perceptual learning models by suggesting a more general perceptual learning process. We propose a rule-based learning model to explain perceptual learning and its specificity and transfer. In this model, a decision unit in high-level brain areas learns the rules of reweighting the V1 inputs through training. However, these rules cannot be applied to a new orientation/location because the decision unit cannot functionally connect to the new V1 inputs that are unattended or even suppressed after training at a different orientation/location, which leads to specificity. Repeated orientation exposure or location training reactivates these inputs to establish the functional connections and enable the transfer of learning.

Microbial communities of activated sludge (AS) play a key role in the performance of wastewater treatment processes. However, seasonal variability of microbial population in varying AS-based processes has been poorly correlated with operation of full-scale wastewater treatment systems (WWTSs). In this paper, significant seasonal variability of AS microbial communities in eight WWTSs located in the city of Guangzhou were revealed in terms of 16S rRNA-based Miseq sequencing. Furthermore, variation redundancy analysis (RDA) demonstrated that the microbial community compositions closely correlated with WWTS operation parameters such as temperature, BOD, NH4+-N and TN. Consequently, support vector regression models which reasonably predicted effluent BOD, SS and TN in WWTSs were established based on microbial community compositions. This work provided an alternative tool for rapid assessment on performance of full-scale wastewater treatment plants.

Although the recently discovered monolayer transition metal dichalcogenides exhibit novel electronic and optical properties, fundamental physical issues such as the quasiparticle bandgap tunability and the substrate effects remain undefined. Herein, we present the report of a quasi-one-dimensional periodically striped superstructure for monolayer MoS2 on Au(100). The formation of the unique striped superstructure is found to be mainly modulated by the symmetry difference between MoS2 and Au(100) and their lattice mismatch. More intriguingly, we find that the monolayer MoS2 is heavily n-doped on the Au(100) facet with a bandgap of 1.3 eV, and the Fermi level is upshifted by ∼0.10 eV on the ridge (∼0.2 eV below the conduction band) in contrast to the valley regions (∼0.3 eV below the conduction band) of the striped patterns after high-temperature sample annealing process. This tunable doping effect is considered to be caused by the different defect densities over the ridge/valley regions of the superstructure. Additionally, an obvious bandgap reduction is observed in the vicinity of the domain boundary for monolayer MoS2 on Au(100). This work should therefore inspire intensive explorations of adlayer-substrate interactions, the defects, and their effects on band-structure engineering of monolayer MoS2.

Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO2 by NO2 is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH3 neutralization or under cloud conditions. Under polluted environments, this SO2 oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH3 and NO2 control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world.

In this work, we present a facile, low-cost, and effective approach to fabricate the UV photodetector with a CuI/ZnO double-shell nanostructure which was grown on common copper microwire. The enhanced performances of Cu/CuI/ZnO core/double-shell microwire photodetector resulted from the formation of heterojunction. Benefiting from the piezo-phototronic effect, the presentation of piezocharges can lower the barrier height and facilitate the charge transport across heterojunction. The photosensing abilities of the Cu/CuI/ZnO core/double-shell microwire detector are investigated under different UV light densities and strain conditions. We demonstrate the I-V characteristic of the as-prepared core/double-shell device; it is quite sensitive to applied strain, which indicates that the piezo-phototronic effect plays an essential role in facilitating charge carrier transport across the CuI/ZnO heterojunction, then the performance of the device is further boosted under external strain.