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Correction for ‘Polyaniline nanorods dotted on graphene oxide nanosheets as a novel super adsorbent for Cr(vi)’ by Shouwei Zhang et al., Dalton Trans., 2013, 42, 7854–7858, https://doi.org/10.1039/C3DT50149C.

Alzheimer’s Disease (AD) is a progressive and irreversible neurodegenerative condition, which results in dementia. Mild Cognitive Impairment (MCI) is an intermediate state between normal aging and AD. Instead of traditional questionnaire method, magnetic resonance imaging (MRI) can be used by radiologists to diagnose and screening AD recently, but long acquisition time is not conducive to screening AD and MCI. To solve this problem, we develop a Fasu-Net (Fast Alzheimer’s disease Screening neural network with Undersampled MRI) for AD and MCI clinical classification. The network uses undersampled structural MRI with a shorter acquisition time to improve the screening and diagnosis efficiency of AD. For achieving the best classification result, three axial planes of brain MR images were feed into the Fasu-Net with transfer learning method. The experiment results on undersampled 3D T1-weighted images database (ADNI) show that in the AD versus MCI versus HC (Healthy Controls) classification, the Fasu-Net achieved the accuracy of 91.41%, thus can be a potential method for fast clinical screening of AD.

The morphological characteristics of retinal vessels are vital for the early diagnosis of pathological diseases such as diabetes and hypertension. However, the low contrast and complex morphology pose a challenge to automatic retinal vessel segmentation. To extract precise semantic features, more convolution and pooling operations are adopted, but some structural information is potentially ignored. In the paper, we propose a novel lightweight pyramid network (LPN) fusing multi-scale features with spatial attention mechanism to preserve the structure information of retinal vessels. The pyramid hierarchy model is constructed to generate multi-scale representations, and its semantic features are strengthened with the introduction of the attention mechanism. The combination of multi-scale features contributes to its accurate prediction. The LPN is evaluated on benchmark datasets DRIVE, STARE and CHASE, and the results indicate its state-of-the-art performance (e.g., ACC of 97.09 $$\%$$ /97.49 $$\%$$ /97.48 $$\%$$ , AUC of 98.79 $$\%$$ /99.01 $$\%$$ /98.91 $$\%$$ on the DRIVE, STARE and CHASE datasets, respectively). The robustness and generalization ability of the LPN are further proved in cross-training experiment. The visualization experiment reveals the semantic gap between various scales of the pyramid and verifies the effectiveness of the attention mechanism, which provide a potential basis for the pyramid hierarchy model in multi-scale vessel segmentation task. Furthermore, the number of model parameters is greatly reduced.

The construction of favorable photoanode configurations is of great importance to enhance the performance of dye-sensitized solar cells (DSSCs). In this work, a double-layer photoanode architecture consisting of a top layer of hierarchical TiO2 networks (HTNs) and a bottom layer of commercial P25 nanoparticles (NPs) was designed and prepared by a facile one-step hydrothermal method. This unique double-layer structure not only affords stronger light scattering and faster electron transport relative to the single-layer P25 photoanode, but also ensures more close contact between different functional layers in contrast to commonly used multistep mechanical coated photoanodes. Furthermore, Au NPs with particle sizes of around 20 nm were incorporated to decorate the HTN photoanode. The localized surface plasmon resonance effect of such Au NPs significantly enhances the light absorption of N719 dye molecules. Benefitted from the splendid light harvesting and superior electron collection, the Au-HTN photoanode configuration delivers an enhanced power conversion efficiency of 5.97%, yielding ∼19% improvement compared to the device based on the conventional P25 photoanode. This work highlights the design of photoanodes with unique nanostructures for enhancing the photovoltaic performance of DSSCs.

An ideal electron transporting layer (ETL) of perovskite solar cells (PSCs) requires reasonable energy levels, high electrical conductivity and excellent charge extraction. The low processing temperature makes ZnO a promising ETL for PSCs; however the widely used solution-processed ZnO films often suffer from high-density surface defect states, which might cause severe charge recombinations at the ETL/perovskite interface and accelerate the chemical decomposition of perovskite materials. In this work, we employed the vacuum-based magnetron sputtering method to deposit ZnO ETLs, which significantly reduces the number of oxygen vacancies and hydroxyl groups on the ZnO surface. The magnetron sputtered ZnO based CH3NH3PbI3 PSCs yield a considerable power conversion efficiency (PCE) of 13.04% with excellent long-term device stability. Furthermore, aiming to improve the ETL/perovskite interface for more efficient electron extraction, a bilayer ZnO/SnO2 ETL was designed for constructing high-efficiency PSCs. The detailed morphology characterization confirms that the bilayer ZnO/SnO2 provides a low-roughness film surface for the deposition of high-quality perovskite films with full coverage and long-range continuity. The carrier dynamic study reveals that the presence of the SnO2 layer results in the formation of favorable cascade energy alignments and facilitates the electron extraction at the ETL/perovskite interface. As a result, compared with the ZnO-based PSCs, the device constructed with the bilayer ZnO/SnO2 ETL delivers an improved PCE of 15.82%, coupled with a reduced hysteresis.

Magnetic resonance imaging (MRI) is widely used to get the information of anatomical structure and physiological function with the advantages of high resolution and non-invasive scanning. But the long acquisition time limits its application. To reduce the time consumption of MRI, compressed sensing (CS) theory has been proposed to reconstruct MRI images from undersampled k-space data. But conventional CS methods mostly use iterative methods that take lots of time. Recently, deep learning methods are proposed to achieve faster reconstruction, but most of them only pay attention to a single domain, such as the image domain or k-space. To take advantage of the feature representation in different domains, we propose a cross-domain method based on deep learning, which first uses convolutional neural networks (CNNs) in the image domain, k-space and wavelet domain simultaneously. The combined order of the three domains is also first studied in this work, which has a significant effect on reconstruction. The proposed IKWI-net achieves the best performance in various combinations, which utilizes CNNs in the image domain, k-space, wavelet domain and image domain sequentially. Compared with several deep learning methods, experiments show it also achieves mean improvements of 0.91 dB in peak signal-to-noise ratio (PSNR) and 0.005 in structural similarity (SSIM).

Application of polarized noble gas technology in lung functional magnetic resonance imaging (fMRI) has garnered attention for its unique advantages, such as high resolution and a lack of radiation exposure. This paper presents a 4-channel radio frequency (RF) coil design method for applications of an 1H/3He MRI system at the ultra-low field of 0.06T. For the complex model of the double-nuclear 1H/3He coil, the analytical optimization method (based on the theories of Biot-Savart law and PSO algorithm) and the electromagnetic (EM) field and radio frequency (RF) circuit co-simulation method was implemented to optimize the analysis, resulting in an effective evaluation. The simulation results demonstrated that the proposed model has the potential for imaging of the lung with the 1H/3He MRI system at an ultra-low field.

The introduction of heteroatoms and functional groups in g-C3N4 generally has great advantages in enhancing the photocatalytic performance. In this work, the heteroatoms (Zn + C) and cyano ( C N) group co-decorated porous g-C3N4 nanosheets (DCNNS) photocatalysts were successfully synthesized through direct calcination of the mixed urea and metal-organic frameworks. The optimized DCNNS displayed a maximum H2 evolution rate of ~484.09 μmol/h with a quantum efficiency of ~3.43% at 420 nm, and the photocatalytic U(VI) reduction activity was improved by ~6.09 times. The enhanced photocatalytic performance could be ascribed to following benefits: (1) the modified DCNNS shared the two-dimensional layered structure of g-C3N4, and the massive nanopores in the nanosheets provided more reaction sites and diffusion channels for accelerated mass transfer; (2) the formation of cyano group greatly broadened the light response range and also acted as strong electron-withdrawing group for improving the carrier separation rate; (3) heteroatoms doping modulated the band gap, increased the electric conductivity, promoted the carrier separation and transport, and prolonged the electron lifetime to enhance photocatalytic performance. This work suggested that the heteroatoms and functional groups co-decoration could significantly improve the performance of g-C3N4-based photocatalysts and hold great potential to be further explored for energy and environmental applications.

Both of planar and mesoporous architectures prevail for perovskite solar cells (PSCs). However, it is still an open question how the architecture affects the performance of PSCs. The inconsistent results in the references often create confusion. In particular, the specific roles of mesoporous frameworks are yet to be well elaborated and require further clarification. In this study, we carefully compared the properties of perovskite films and the device performances for both architectures to unravel the roles of mesoporous TiO2 framworks in CH3NH3PbI3 PSCs. The detailed characterizations of structural, microscopic, optical and electrical properties revealed that the presence of mesoporous TiO2 framework contributed to enlarged perovskite crystal sizes, enhanced light harvesting, efficient electron extration and suppressed charge recombination. As a result, compared with the planar device, the mesoporous device yielded an improved power conversion efficiency of 18.18%, coupled with a reduced hystersis. This study reveals the benefits of mesoporous TiO2 framework in PSCs and provides the guidance for the design and optimization of architectures for high-performance devices.

All solid-state quantum dot-sensitized solar cells (QDSCs) have become increasingly attractive owing to their ability to solve the issues of package difficulty and poor long-term stability. However, the commonly used colloidal lead sulfide (PbS) quantum dots (QDs) suffer from having a complicated synthesis with the use of high-temperature, harmful organic solvents and a protective atmosphere. In this work, the synchronous deposition of PbS and CdS QDs, realized through a facile successive ionic layer adsorption and reaction (SILAR), was proposed to construct efficient and stable solid-state QDSCs. This design concept affords two benefits: (1) the synchronous deposition of two sulfides suppresses the excessive growth of PbS QDs in the mesopores of films, thereby ensuring the efficient electron injection from PbS to TiO2; (2) the intimate interpenetration of two sulfides allows superior passivation of high-density defects on the surface of PbS QDs, which reduces the severe interfacial charge recombination. As a result, the solid-state (Pb,Cd)S QD-sensitized TiO2 solar cell achieved more than 5 times efficiency enhancement in contrast to the conventional PbS/CdS pattern based device. This work highlights the design of novel QD schemes for high performance solid-state solar cells.

CuSbS2 thin films were fabricated by spray pyrolysis from metal chloride aqueous solutions, followed by a post-deposition sulfurization step. The structural, chemical, optical and electrical properties of CuSbS2 and the effect of various sulfurization temperatures on CuSbS2 thin film have been systematically studied. We used a two-step sulfurization method. Step 1 at lower temperature was to encourage complete saturation of the as-deposited film with sulfur vapor. And step 2 at higher temperature was to promote the formation and crystallization of CuSbS2. The sulfurization temperature of step 2 is very important for the formation of device-grade CuSbS2 films. With the increase in sulfurization temperature, impurities such as Sb2S3 decreased and the crystallinity of CuSbS2 improved. Until 400 °C, impurities disappeared and phase-pure well-crystallinity CuSbS2 thin films were obtained. When the sulfurization temperature is higher than 400 °C, CuSbS2 gradually changes to Cu3SbS4. The CuSbS2 films sulfurized at 400 °C with optimum band gap of 1.53 eV are p type, and absorption coefficient is larger than 105 cm−1 in the visible light wavelength range. The temperature dependence of electrical conductivity of CuSbS2 has been studied for the first time. At measurement temperatures higher than 140 K the electrical conductivity of the CuSbS2 film is dominated by band conduction and nearest neighbor hopping (NNH). However, at temperatures below 140 K the conduction is predominantly affected by variable range hopping (VRH). Finally, thin-film solar cells based on the sprayed CuSbS2 absorber layers with a maximum photoelectric conversion efficiency of 0.34% have been fabricated.

Compressed sensing magnetic resonance imaging (CS-MRI) greatly accelerates the acquisition process and yield considerable reconstructed images. Deep learning was introduced into CS-MRI to further speed up the reconstruction process and improve the image quality. Recently, generative adversarial network (GAN) using two-stage cascaded U-Net structure as generator has been proven to be effective in MRI reconstruction. However, previous cascaded structure was limited to few feature information propagation channels thus may lead to information missing. In this paper, we proposed a GAN-based model, DBGAN, for MRI reconstruction from undersampled k-space data. The model uses cross-stage skip connection (CSSC) between two end-to-end cascaded U-Net in our generator to widen the channels of feature propagation. To avoid discrepancy between training and inference, we replaced classical batch normalization (BN) with instance normalization (IN) . A stage loss is involved in the loss function to boost the training performance. In addition, a bilinear interpolation decoder branch is introduced in the generator to supplement the missing information of the deconvolution decoder. Tested under five variant patterns with four undersampling rates on different modality of MRI data, the quantitative results show that DBGAN model achieves mean improvements of 3.65 dB in peak signal-to-noise ratio (PSNR) and 0.016 in normalized mean square error (NMSE) compared with state-of-the-art GAN-based methods on T1-Weighted brain dataset from MICCAI 2013 grand challenge. The qualitative visual results show that our method can reconstruct considerable images on brain and knee MRI data from different modality. Furthermore, DBGAN is light and fast - the model parameters are fewer than half of state-of-the-art GAN-based methods and each 256 × 256 image is reconstructed in 60 milliseconds, which is suitable for real-time processing.

Correction for ‘Rationally designed 1D Ag@AgVO3 nanowire/graphene/protonated g-C3N4 nanosheet heterojunctions for enhanced photocatalysis via electrostatic self-assembly and photochemical reduction methods’ by Shouwei Zhang et al., J. Mater. Chem. A, 2015, 3, 10119–10126, https://doi.org/10.1039/C5TA00635J.

Compressed sensing (CS) is a technique to reconstruct images from undersampling data, reducing the scanning time of magnetic resonance imaging (MRI). It utilizes the sparsity of images in some transform domains. Total variation (TV) has been applied to enforce sparsity. However, traditional TV based on the l1-norm is not the most direct way to induce sparsity, and it cannot offer a sufficiently sparse representation. Since the lp-norm (0< p < 1) promotes the sparsity better than that of the l1-norm, we propose two extended TV algorithms based on the lp-norm: anisotropic and isotropic total p-variation (TpV). Then we introduce them to the MRI reconstruction model. We apply the Bregman iteration technique to handle the proposed optimization problem. During the iteration, the p-shrinkage operator is employed to resolve the nonconvex problem caused by the lp-norm. Experimental results illustrate that our algorithms could offer the higher SNR and lower relative error compared with traditional TV algorithms and high-degree TV (HDTV) algorithm in MRI reconstruction problem.

Urchin-like TiO2 hierarchical microspheres (UTHMs) with an extremely large surface area of 331 m2 g−1 were synthesized via a facile one-pot hydrothermal method and studied for dye-sensitized solar cells (DSSCs) application. In-situ growth of Au nanoparticles (NPs) on the surface of the UTHMs were further conducted to achieve Au-decorated UTHMs (Au-UTHMs). A series of novel composite photoanode films were designed through the combined use of Au-UTHMs and UTHMs at different mass ratios. The DSSC constructed with the composite photoanode prepared under an optimal Au-UTHMs to UTHMs ratio of 2 wt% yields a considerable power conversion efficiency of 7.21%, which was markedly higher than that of the pure P25 NPs based device (5.19%) and pure UTHMs based device (6.10%). The significantly enhanced performance of the composite photoanode based DSSC can be attributed to the synergistic effect of two benefits: (1) the large specific surface area, strong light scattering and fast electron transfer channels arising from the novel hierarchical features of UTHMs, and (2) the enhanced light absorption owing to the localized surface plasmon resonance (LSPR) effect of Au NPs.

Semiconductor quantum dots (QDs) and organic-inorganic halide perovskites have emerged as two important families of excellent photovoltaic materials and contributed to the rapid progress in photovoltaic field during the past decade. This review seeks to provide an insight into an advanced concept on the synergistic combination of QDs and perovskites, which affords a number of exciting synergies for the further advancements in hybrid solar cells, including growth promotion of perovskite crystals, complementary light harvesting, rapid extraction of charge carriers, efficient carrier transport, surface and interface engineering, and improved stability. The emphasis is placed on the most widely studied system of PbS and CH3NH3PbI3, which enables the heteroepitaxial growth of perovskites on QDs. Issues related to fundamental physical and chemical features, lattice coherence, materials and films processing, and energy transfer between QDs and perovskites, as well as advances in device architecture and photovoltaic performance are discussed. In addition, prospects overriding current challenges are also proposed for future work toward practical realization of highly efficient and stable hybrid solar cells.

Two-dimensional Indium selenide (2D In2Se3), a direct band gap semiconductor in group III-VI, shows a potential application in constructing novel photodetectors with broadband spectral response. The device performances of these In2Se3-based photodetectors are limited by synthesis of the large-scale In2Se3 with high crystal quality and optimization of device structure and constructing process. Herein, a vertical β-In2Se3/Si p-n heterojunction is reported by in situ depositing a β-In2Se3 film with high quality on Si substrate by pulsed laser deposition technique. The resultant β-In2Se3/Si p-n heterojunction showed a broadband spectral response range from 265 nm to 1300 nm with a high responsivity up to 6.4 AW-1 at bias of −2 V. More importantly, a high response speed approaching to 2.2 μs at zero bias is achieved, which are much better than most of previous III-VI/Si based photodetectors and some of 2D layered transition metal dichalcogenides (TMDCs)/Si heterojunction. Moreover, the responsivity for 1300 nm NIR light is as large as 0.12 AW-1, which is superior than most of previous Si compatible 2D-3D heterojunction. The results suggest that our work paves the way toward the construction of novel III-VI/Si 2D-3D heterojunctions for high-performance and broadband photodetectors.

Magnetic Resonance Imaging (MRI) has been developed for many years as an indispensable clinical examination method. Long detection time has always been an obstacle in the development of MRI. In recent years, the application of deep learning in MRI reconstruction has significantly improved the speed and quality of reconstruction. In this paper, we propose a new GAN-based deep learning method called RAGAN. In our RAGAN structure, we innovatively join residual-ASPP blocks and the gradient information guided loss for a better reconstruction effect of texture and detailed information at different scales. We have performed comparison studies with conventional CS-MRI reconstruction methods and deep learning based methods. From the subjective and objective reconstruction results, our method has a better reconstruction effect than the comparison methods.

The introduction of heteroatoms and functional groups in g-C

In this work, we report an electrodeposition technique for fabricating chalcopyrite phase CuInSe 2 (CISe) thin films and demonstrate the great prospect of CISe films for serving as efficient counter electrodes (CEs) in quantum dot sensitized solar cells (QDSCs). The as-prepared CISe materials, directly deposited onto conducting substrates, display long-range uniformity with high crystallinity and nanopillar shapes. A CISe CE-based CdS/CdSe QDSC delivers a considerable power conversion efficiency of 2.92%, coupled with excellent device stability. In contrast to the conventional noble Pt electrodes, CISe CEs exhibit much higher catalytic activity for electrocatalysing polysulfide electrolyte regeneration. This work offers a promising CE with superior catalytic capability for constructing highly efficient and stable QDSCs.

Novel amino-modified rice bran biochar/MgFeAlO4 (RB@MgFeAlO4-NH2) magnetic composites were synthesized via a simple one-step solvothermal approach and applied for removing toxic Ni(II) from wastewater. The elimination process and sorption performance of Ni(II) on RB@MgFeAlO4-NH2 were analyzed by combining batch experiments and spectral techniques. The sorption isotherms and kinetic data indicated that Ni(II) sorption on RB@MgFeAlO4-NH2 was monolayer and rapid. The experimental results confirmed that the obtained RB@MgFeAlO4-NH2 magnetic composite had high sorption capacity for Ni(II). The maximum sorption capacity of Ni(II) on RB@MgFeAlO4-NH2 was 201.62 mg g−1. The researches based on the sorption mechanism showed that the ion exchange mechanism accounted for 76.51% of Ni(II) sorption. In addition, the amino, carboxyl and hydroxyl functional groups were also involved in the complexation with Ni(II). In view of its multiple advantages of environmental friendliness, low cost, easy magnetic separation and high sorption capacity, RB@MgFeAlO4-NH2 will be an excellent adsorbent for low-cost and efficient elimination of Ni(II) from aqueous solutions.

Panchromatic solar cells are of great prospects in virtue of the sufficient utilization of solar energy. The narrow bandgap semiconductors such as PbS can serve as promising candidates for light harvesting. In this paper, we report an in situ seeded growth of PbS quantum dots (QDs) onto TiO2 films for the construction of high-performance PbS/CdS QD-sensitized solar cells. Careful morphologic, optical, and electrical examinations were performed to probe into the superiority of such an approach. The predeposited PbSO3 seeds are used as nucleation sites for monodisperse PbS QDs with the particle size of ∼3.5 nm, which ensures favorable electron injection from PbS into TiO2. Meanwhile, the CdS passivation layer is synchronously loaded along with in situ seeded PbS, resulting in effective passivation of defect states at the PbS surface. Eventually, benefitted from improved carrier manipulation (i.e., electron injection and charge transport), the in situ seeded device yields a power conversion efficiency of 2.13%, exhibiting considerably enhanced photovoltaic performance in contrast to the identical PbS/CdS scheme processed by the conventional two-step successive ionic layer adsorption and reaction.

In this work, high crystallinity copper selenide thin films directly deposited onto conducting substrates were obtained through a potentiostatic electrodeposition approach. The as-deposited copper selenides involve annealing induced phase transformation from tetragonal Cu3Se2 to cubic Cu2-xSe. The annealing also leads to a remarkable morphology change from dendritic nanosheets to connected networks and separated particle shapes for the annealed (A-Cu2-xSe) and selenized (S-Cu2-xSe) samples, respectively. The copper selenide thin films were demonstrated to serve as efficient counter electrodes (CEs) in quantum dot-sensitized solar cells (QDSCs) for electrocatalyzing polysulfide electrolyte regeneration. The CdS/CdSe QDSCs constructed with copper selenide CEs deliver considerable power conversion efficiencies (PCEs), especially an optimal value of 3.89% for the A-Cu2-xSe CE-based device. The enhanced photovoltaic performance benefits from the connected network microstructure of A-Cu2-xSe films which afford a large number of reaction sites and efficient charge transport pathways. The Tafel polarization characterization further indicates that, in contrast to the commonly used Cu2S and Pt CEs, the non-stoichiometric Cu2-xSe CE exhibits better electrochemical catalytic activity. This work highlights the great potential of electrodeposition for fabricating promising copper selenide CEs for high performance QDSCs.

In this study, layered porous ZnO microspheres, instead of traditional zinc ions, were used to obtain a composite of nano-ZnO and a metal organic framework (Zn-MOF-74), namely ZnO-NP@Zn-MOF-74. Compared with the traditional Zn-MOF-74, the ZnO-NP@Zn-MOF-74 showed better removal performances for both copper (Cu) and tetracycline (TC) due to its smaller size and good affinities of the loaded nano-ZnO. Batch experiments showed that the simultaneous removal of Cu and TC by the ZnO-NP@Zn-MOF-74 was rapid and pH-dependent. The removal efficiencies of both Cu and TC increased rapidly during the first 10 min and could reach equilibriums within 2 h. The maximum sorption capacities of Cu and TC on the ZnO-NP@Zn-MOF-74 derived from the Langmuir model were 106.27 and 137.17 mg·g−1, respectively. The removal mechanisms for Cu and TC involved surface complexation, π-π stacking, ion exchange, and electrostatic interaction. In addition, the formation of the ZnO-NP@Zn-MOF-74-Cu-TC complex on the surface of the ZnO-NP@Zn-MOF-74 improved the removal of both TC and Cu. Given the above results, the ZnO-NP@Zn-MOF-74 has great application prospects for the treatment of Cu and TC polluted water.

In this study, three-dimensional flower-like α-Fe2O3 (F-Fe2O3) microspheres were synthesized by a facile chemical bath method and characterized by XRD, FE-SEM, TEM and BET specific surface area. The maximum sorption capacity of 60Co(II) on F-Fe2O3 reached to 6.78 × 10−4 mol/g at 298 K and pH 6.5. The pH and ionic strength experiments implied that the removal of F-Fe2O3 towards 60Co(II) is dominated by ion exchange and/or outer-sphere surface complexation at pH 7.5. In conclusion, the F-Fe2O3 microspheres could be applied as cost-effective materials for the removal of 60Co(II) from wastewater.

Low bandgap PbS quantum dots (QDs) have attracted special interests serving as promising sensitizers for developing high performance near-infrared responsive photovoltaics. However, the commonly studied successive ionic layer adsorption and reaction (SILAR) processed PbS QD-sensitized solar cells (QDSCs) constructed with mesoporous TiO 2 nanoparticle-photoelectrodes generally experience poor fill factor (FF) values lower than 0.50, arising from severe interfacial charge recombination because of the structural disorder of nanoparticles. This work demonstrates the construction of aligned TiO 2 nanorod arrays (NRAs), vertically grown on substrates, for SILAR processed PbS QDSCs with high FF. The microscopic, structural, and optical characterizations reveal a rutile phase of single-crystalline structure in nature for TiO 2 NRAs. The as-designed solar cell affords the advantages of panchromatic absorption for adequate light harvesting, reasonable band structure for efficient electron injection, and one dimensional (1D) oriented architecture for radial directional charge transport. A solar cell based on a 1.9 μm TiO 2 NRA photoelectrode yields a considerable power conversion efficiency of 1.15% under 1 sun, coupled with a significantly enhanced FF of 0.51 in contrast to a conventional TiO 2 nanoparticle-based device (FF = 0.38). The high FF is attributed to the outstanding electron transport behavior from QD sensitizers to conducting substrates via a shortest pathway (i.e., through radial direction of NRAs), thereby suppressing charge recombinations in solar devices. Therefore, the architecture of aligned 1D TiO 2 NRAs is of great prospect to construct high performance PbS QDSCs. The performance improvement is promisingly expected through fully understanding of the radial directional charge transport mechanism and further optimization of NRA photoelectrodes and QD assemblies.

In contrast with the commonly used TiO 2 or ZnO electron transporters, SnO 2 , which possesses relatively low conduction band and high electron-mobility, is expected to facilitate the extraction of photogenerated electrons from quantum dots (QDs) to oxides in quantum dot-sensitized solar cells (QDSCs), especially for those narrow band gap QDs (e.g., PbS). In this work, hierarchical SnO 2 hollow sub-microspheres have been synthesized by a facile one-step hydrothermal process, and further studied for near infrared responsive PbS QDSCs. Morphology and structure characterizations reveal that these sub-micrometer-sized spheres (150–200 nm) with hollow interiors are assembled by numerous packed nanograins. The nanometer-sized grains ensure large specific surface area (∼69.2 m 2 g −1 ) and pore size (∼19 nm) for high QD loading, while the sub-micrometer-sized spheres function as efficient light scatters and robust electron transporting structures. As a result, these superior features make such hierarchical SnO 2 architectures very promising candidates for photovoltaic application. Based on the multifunctional photoelectrode constructed with hierarchical SnO 2 hollow architectures, an appreciable power conversion efficiency up to 1.34% has been achieved for a PbS QDSC, coupled with interface engineering through TiO 2 coating and CdS passivation. This work offers a promising design for developing high performance QDSCs.

Near-infrared responsive PbS quantum dots (QDs) have received particular attention serving as promising candidates for next generation photovoltaics. This work explores a novel anion-exchange strategy to produce high quality in-situ grown PbS QDs on mesoporous TiO2 films. Such an anion-exchange reaction occurs between PbSO3 and S2− in aqueous solution at low temperature under ambient conditions. A solar cell based on such anion-exchanged PbS QDs yields an impressive power conversion efficiency of 3.06% without resorting to any doping or co-sensitization, achieving around 200% performance improvement with respect to that of a conventional successive ionic layer adsorption and reaction (SILAR) processed device. Based on detailed microscopic, optical and electrochemical characterizations, much enhanced photovoltaic performance is attributed to improved electron injection and collection efficiencies. Up-shifted conduction band level of reasonable small-sized PbS QDs processed by anion-exchange gives rise to desired electron injection from PbS to TiO2, while simultaneous deposition of ZnS passivation layer along with the formation of anion-exchanged PbS QDs allows the minimization of interface states for reduced charge recombination. This work offers an alternative promising approach for constructing high performance PbS QD-sensitized solar cells.

Herein, the hydrothermal method was adopted to synthesize Fe3O4@MnO2 hollow spheres for the removal of U(VI) from aqueous solution. The effects of contact time, pH, ionic strength, solid content and temperature were investigated by using a batch technique. The sorption of U(VI) was dependent on ionic strength at pH 7 pointed to the occurrence of inner-sphere surface complexation. Typical sorption isotherms (Langmuir, Freundlich, Dubinin-Raduskevich) were determined for the mechanism of sorption process. The maximum sorption amount of U(VI) on Fe3O4@MnO2 hollow spheres reached to 13.95 mg/g at 293 K. The thermo-dynamic parameters were calculated from the temperature isotherms, and the results suggested that U(VI) sorption on Fe3O4@MnO2 hollow spheres was a spontaneous and endothermic process. The results might be important for the application for U(VI) pollution management.

PbS is a promising light harvester for near-infrared (NIR) responsive quantum dot (QD) photovoltaics due to its narrow bulk band gap (0.41 eV) and large exciton Bohr radius (18 nm). However, the relatively low conduction band (CB) and high-density surface defects of PbS as two major drawbacks for its use in solar cells severely hamper the photovoltaic performance enhancement. In this work, a modified solution-based successive ionic layer adsorption and reaction (SILAR) utilizing mixed cationic precursors of Pb2+ and Cd2+ is explored, and such a scheme offers two benefits, band-structure tailoring and surface passivation. In-situ deposited CdS suppresses the excessive growth of PbS in the mesopores, thereby facilitating the favorable electron injection from PbS to TiO2 in view of the up-shifted CB level of QDs; the intimate interpenetration of two sulfides with each other leads to superior passivation of trap state defects on PbS, which suppresses the interfacial charge recombination. With the construction of photovoltaics based on such a hybrid (Pb,Cd)S/CdS configuration, impressive power conversion efficiency up to 4.08% has been reached, outperforming that of the conventional PbS/CdS pattern (2.95%). This work highlights the great importance of band-structure tailoring and surface passivation for constructing highly efficient PbS QD photovoltaics.

Compressed sensing magnetic resonance imaging (CS-MRI) reduces the time to obtain reconstructed images by under sampling the k-space data. However, solving the ill-posed problem requires an expensive computational cost. Currently, state-of-the-art compressed sensing analysis uses deep learning-based methods to reconstruct magnetic resonance images, which achieves a great success. In this paper, we propose a novel network architecture named EAGAN based on the generative adversarial networks (GAN). This proposed model enhances antagonism between the generator and the discriminator. In particular, we introduce perceptual loss to update network parameters, which makes the texture of reconstructed image reaching a better level. In addition, residual learning strategies were adopted to improve learning efficiency and reconstruction quality. Our method obtained promising experimental results on both imaging quality and reconstruction speed for 1.5T brain MRI while only 20 percent of the raw k-space data are sampled using Gaussian random sampling mask. Each image is reconstructed in about 20 ms, which is suitable for real-time processing.

The main idea of RPCA (Robust Principal Component Analysis) is to decompose a matrix into a low-rank component L and a sparse component S. In dynamic MRI (Magnetic Resonance Imaging) reconstructions, due to the regular movement or pulsation of organs, the change is relatively slight and the similarity between frames is very high. Therefore, the RPCA model is very suitable for the reconstruction of dynamic MR images. However, for static images, their low-rank attribute is not obvious and we cannot achieve better results if we apply the RPCA model to the reconstruction of static images directly. Based on the non-local self-similarity and sparsity of an image, this paper successfully applied the RPCA model to the reconstruction of static MR images and achieved good reconstruction results.