Concentrated Solar Light Photoelectrochemical Water Splitting for Stable and High-Yield Hydrogen Production.

Photoelectrochemical water splitting is a promising technique for converting solar energy into low-cost and eco-friendly H2 fuel. However, the production rate of H2 is limited by the insufficient number of photogenerated charge carriers in the conventional photoelectrodes under 1 sun (100 mW cm-2 ) light. Concentrated solar light irradiation can overcome the issue of low yield, but it leads to a new challenge of stability because the accelerated reaction alters the surface chemical composition of photoelectrodes. Here, it is demonstrated that loading Pt nanoparticles (NPs) on single crystalline GaN nanowires (NWs) grown on n+ -p Si photoelectrode operates efficiently and stably under concentrated solar light. Although a large number of Pt NPs detach during the initial reaction due to H2 gas bubbling, some Pt NPs which have an epitaxial relation with GaN NWs remain stably anchored. In addition, the stability of the photoelectrode further improves by redepositing Pt NPs on the reacted Pt/GaN surface, which results in maintaining onset potential >0.5 V versus reversible hydrogen electrode and photocurrent density >60 mA cm-2 for over 1500 h. The heterointerface between Pt cocatalysts and single crystalline GaN nanostructures shows great potential in designing an efficient and stable photoelectrode for high-yield solar to H2 conversion.

Water-promoted selective photocatalytic methane oxidation for methanol production.

Converting relatively inert methane into active chemical fuels such as methanol with high selectivity through an energy-saving strategy has remained a grand challenge. Photocatalytic technology consuming solar energy is an appealing alternative for methane reforming. However, the low efficiency and the undesirable formation of low-value products, such as carbon dioxide and ethane, limit the commercial application of photocatalytic technology. Herein, we find a facile and practical water-promoted pathway for photocatalytic methane reforming into methanol, enabling methanol production from methane and oxygen with a high selectivity (>93%) and production rate (21.4 µmol cm-2 h-1 or 45.5 mmol g-1 h-1) on metallic Ag nanoparticle-loaded InGaN nanowires (Ag/InGaN). The experimental XPS and theoretical PDOS analyses reveal that water molecules adsorbed on Ag nanoparticles (AgNPs) can promote the electron transfer from InGaN to AgNPs, which enables the formation of partial Ag species with a lower oxidation state in AgNPs. Through the in situ IR spectrum and the reaction pathway simulation studies, these newly formed Ag species induced by water adsorption were demonstrated to be responsible for the highly selective methanol production due to the effective formation of a C-O bond and the optimal desorption of the formed methanol from the surface indium site of the InGaN photocatalyst. This unique water promotion effect leads to a 55-fold higher catalytic rate and 9-fold higher selectivity for methanol production compared to photocatalytic methane reforming without water addition. This finding offers a new pathway for achieving clean solar fuels by photocatalysis-based methane reforming.

Oxynitrides enabled photoelectrochemical water splitting with over 3,000 hrs stable operation in practical two-electrode configuration.

Solar photoelectrochemical reactions have been considered one of the most promising paths for sustainable energy production. To date, however, there has been no demonstration of semiconductor photoelectrodes with long-term stable operation in a two-electrode configuration, which is required for any practical application. Herein, we demonstrate the stable operation of a photocathode comprising Si and GaN, the two most produced semiconductors in the world, for 3,000 hrs without any performance degradation in two-electrode configurations. Measurements in both three- and two-electrode configurations suggest that surfaces of the GaN nanowires on Si photocathode transform in situ into Ga-O-N that drastically enhances hydrogen evolution and remains stable for 3,000 hrs. First principles calculations further revealed that the in-situ Ga-O-N species exhibit atomic-scale surface metallization. This study overcomes the conventional dilemma between efficiency and stability imposed by extrinsic cocatalysts, offering a path for practical application of photoelectrochemical devices and systems for clean energy.

Solar-to-hydrogen efficiency of more than 9% in photocatalytic water splitting.

Production of hydrogen fuel from sunlight and water, two of the most abundant natural resources on Earth, offers one of the most promising pathways for carbon neutrality1-3. Some solar hydrogen production approaches, for example, photoelectrochemical water splitting, often require corrosive electrolyte, limiting their performance stability and environmental sustainability1,3. Alternatively, clean hydrogen can be produced directly from sunlight and water by photocatalytic water splitting2,4,5. The solar-to-hydrogen (STH) efficiency of photocatalytic water splitting, however, has remained very low. Here we have developed a strategy to achieve a high STH efficiency of 9.2 per cent using pure water, concentrated solar light and an indium gallium nitride photocatalyst. The success of this strategy originates from the synergistic effects of promoting forward hydrogen-oxygen evolution and inhibiting the reverse hydrogen-oxygen recombination by operating at an optimal reaction temperature (about 70 degrees Celsius), which can be directly achieved by harvesting the previously wasted infrared light in sunlight. Moreover, this temperature-dependent strategy also leads to an STH efficiency of about 7 per cent from widely available tap water and sea water and an STH efficiency of 6.2 per cent in a large-scale photocatalytic water-splitting system with a natural solar light capacity of 257 watts. Our study offers a practical approach to produce hydrogen fuel efficiently from natural solar light and water, overcoming the efficiency bottleneck of solar hydrogen production.

Pt nanoclusters on GaN nanowires for solar-asssisted seawater hydrogen evolution.

Seawater electrolysis provides a viable method to produce clean hydrogen fuel. To date, however, the realization of high performance photocathodes for seawater hydrogen evolution reaction has remained challenging. Here, we introduce n+-p Si photocathodes with dramatically improved activity and stability for hydrogen evolution reaction in seawater, modified by Pt nanoclusters anchored on GaN nanowires. We find that Pt-Ga sites at the Pt/GaN interface promote the dissociation of water molecules and spilling H* over to neighboring Pt atoms for efficient H2 production. Pt/GaN/Si photocathodes achieve a current density of -10 mA/cm2 at 0.15 and 0.39 V vs. RHE and high applied bias photon-to-current efficiency of 1.7% and 7.9% in seawater (pH = 8.2) and phosphate-buffered seawater (pH = 7.4), respectively. We further demonstrate a record-high photocurrent density of ~169 mA/cm2 under concentrated solar light (9 suns). Moreover, Pt/GaN/Si can continuously produce H2 even under dark conditions by simply switching the electrical contact. This work provides valuable guidelines to design an efficient, stable, and energy-saving electrode for H2 generation by seawater splitting.

S2C-DeLeNet: A parameter transfer based segmentation-classification integration for detecting skin cancer lesions from dermoscopic images.

Dermoscopic images ideally depict pigmentation attributes on the skin surface which is highly regarded in the medical community for detection of skin abnormality, disease or even cancer. The identification of such abnormality, however, requires trained eyes and accurate detection necessitates the process being time-intensive. As such, computerized detection schemes have become quite an essential, especially schemes which adopt deep learning tactics. In this paper, a convolutional deep neural network, S2C-DeLeNet, is proposed, which (i) Performs segmentation procedure of lesion based regions with respect to the unaffected skin tissue from dermoscopic images using a segmentation sub-network, (ii) Classifies each image based on its medical condition type utilizing transferred parameters from the inherent segmentation sub-network. The architecture of the segmentation sub-network contains EfficientNet-B4 backbone in place of the encoder and the classification sub-network bears a 'Classification Feature Extraction' system which pulls trained segmentation feature maps towards lesion prediction. Inside the classification architecture, there have been designed, (i) A 'Feature Coalescing Module' in order to trail and mix each dimensional feature from both encoder and decoder, (ii) A '3D-Layer Residuals' block to create a parallel pathway of low-dimensional features with high variance for better classification. After fine-tuning on a publicly accessible dataset, a mean dice-score of 0.9494 during segmentation is procured which beats existing segmentation strategies and a mean accuracy of 0.9103 is obtained for classification which outperforms conventional and noted classifiers. Additionally, the already fine-tuned network demonstrates highly satisfactory results on other skin cancer segmentation datasets while cross-inference. Extensive experimentation is done to prove the efficacy of the network for not only dermoscopic images but also different medical modalities; which can show its potential in being a systematic diagnostic solution in the field of dermatology and possibly more.

Metal-Support Interaction-Promoted Photothermal Catalytic Methane Reforming into Liquid Fuels.

Clean and renewable photocatalytic technology for methane reforming into high-value liquid fuels, such as methanol, is a promising strategy for commercial industrial applications. However, poor charge separation, sluggish methane activation, and excessive oxidation collectively inhibit the production of methanol from photocatalytic methane reforming. Herein, we have developed enhanced metal-support interactions between a GaN nanowire photocatalyst and a Cu nanoparticle (CuNP) cocatalyst via p-doping in GaN. CuNP-loaded p-type GaN (Cu/p-GaN) with enhanced metal-support interaction has 3.5-fold higher activity (12.8 mmol g-1 h-1, higher than previous reports) for methanol production in photothermal catalytic methane reforming with oxygen as an oxidant and sunlight as the sole energy source than CuNP-loaded intrinsic GaN (Cu/i-GaN) or n-type GaN (Cu/n-GaN). In-situ IR measurements indicate that enhanced metal-support interaction significantly promotes activation of methane and formation of methanol. Combining with X-ray photoelectron spectroscopy (XPS), density functional theory (DFT) simulations demonstrate that this enhanced metal-support interaction in Cu/p-GaN greatly improves electron transfer from p-GaN photocatalysts to the 3d states of CuNP cocatalysts through the interface between them. Catalytic pathway simulations further reveal that the enhanced metal-support interaction in Cu/p-GaN also desirably decreases the reaction energy of rate-determining methanol desorption, which decreases the excessive oxidation of the produced methanol and accelerates the regeneration of surface catalytic sites. These studies and findings offer critical insights into the design and development of metal nanoparticle-loaded photocatalysts for photocatalysis-based methane reforming into methanol.

Crystallographic Effects of GaN Nanostructures in Photoelectrochemical Reaction.

Tuning the surface structure of the photoelectrode provides one of the most effective ways to address the critical challenges in artificial photosynthesis, such as efficiency, stability, and product selectivity, for which gallium nitride (GaN) nanowires have shown great promise. In the GaN wurtzite crystal structure, polar, semipolar, and nonpolar planes coexist and exhibit very different structural, electronic, and chemical properties. Here, through a comprehensive study of the photoelectrochemical performance of GaN photocathodes in the form of films and nanowires with controlled surface polarities we show that significant photoelectrochemical activity can be observed when the nonpolar surfaces are exposed in the electrolyte, whereas little or no activity is measured from the GaN polar c-plane surfaces. The atomic origin of this fundamental difference is further revealed through density functional theory calculations. This study provides guideline on crystal facet engineering of metal-nitride photo(electro)catalysts for a broad range of artificial photosynthesis chemical reactions.

CuS-Decorated GaN Nanowires on Silicon Photocathodes for Converting CO2 Mixture Gas to HCOOH.

Hybrid materials consisting of semiconductors and cocatalysts have been widely used for photoelectrochemical (PEC) conversion of CO2 gas to value-added chemicals such as formic acid (HCOOH). To date, however, the rational design of catalytic architecture enabling the reduction of real CO2 gas to chemical has remained a grand challenge. Here, we report a unique photocathode consisting of CuS-decorated GaN nanowires (NWs) integrated on planar silicon (Si) for the conversion of H2S-containing CO2 mixture gas to HCOOH. It was discovered that H2S impurity in the modeled industrial CO2 gas could lead to the spontaneous transformation of Cu to CuS NPs, which resulted in significantly increased faradaic efficiency of HCOOH generation. The CuS/GaN/Si photocathode exhibited superior faradaic efficiency of HCOOH = 70.2% and partial current density = 7.07 mA/cm2 at -1.0 VRHE under AM1.5G 1 sun illumination. To our knowledge, this is the first demonstration that impurity mixed in the CO2 gas can enhance, rather than degrade, the performance of the PEC CO2 reduction reaction.

Sleep Apnea Event Detection from Sub-frame Based Feature Variation in EEG Signal Using Deep Convolutional Neural Network.

The topic of automatic detection of sleep apnea which is a respiratory sleep disorder, affecting millions of patients worldwide, is continuously being explored by researchers. Electroencephalogram signal (EEG) represents a promising tool due to its direct correlation to neural activity and ease of extraction. Here, an innovative approach is proposed to automatically detect apnea by incorporating local variations of temporal features for identifying the global feature variations over a broader window. An EEG data frame is divided into smaller sub-frames to effectively extract local feature variation within one larger frame. A fully convolutional neural network (FCNN) is proposed that will take each sub-frame of a single frame individually to extract local features. Following that, a dense classifier consisting of a series of fully connected layers is trained to analyze all the local features extracted from subframes for classifying the entire frame as apnea/non-apnea. Finally, a unique post-processing technique is applied which significantly improves accuracy. Both the EEG frame length and post-processing parameters are varied to find optimal detection conditions. Large-scale experimentation is executed on publicly available data of patients with varying apnea-hypopnea indices for performance evaluation of the suggested method.

Genotype-phenotype correlation of ß-lactamase-producing uropathogenic Escherichia coli (UPEC) strains from Bangladesh.

Escherichia coli is a pathogen commonly encountered in clinical laboratories, and is capable of causing a variety of diseases, both within the intestinal tract (intestinal pathogenic strains) and outside (extraintestinal pathogenic E. coli, or ExPEC). It is associated with urinary tract infections (UTIs), one of the most common infectious diseases in the world. This report represents the first comparative analysis of the draft genome sequences of 11 uropathogenic E. coli (UPEC) strains isolated from two tertiary hospitals located in Dhaka and Sylhet, Bangladesh, and is focused on comparing their genomic characteristics to each other and to other available UPEC strains. Multilocus sequence typing (MLST) confirmed the strains belong to ST59, ST131, ST219, ST361, ST410, ST448 and ST4204, with one of the isolates classified as a previously undocumented ST. De novo identification of the antibiotic resistance genes blaNDM-5, blaNDM-7, blaCTX-M-15 and blaOXA-1 was determined, and phenotypic-genotypic analysis of virulence revealed significant heterogeneity within UPEC phylogroups.

Dataset concerning effects of stevia (Stevia rebaudiana bertoni), amlodipine, losartan, and valsartan on water consumption, blood glucose and heart tissue in gentamycin-induced nephrotoxicity in the rat model.

This dataset indicates the effect of stevia (Stevia rebaudiana Bertoni); angiotensin-II type-1 receptor (AT1) blockers, losartan and valsartan; and a calcium (Ca2+) channel blocker, amlodipine; on water consumption, fasting blood glucose, and cardiac histology in gentamycin-induced nephrotoxic rat model. Six groups of male Sprague-Dawley rats were selected as sham control group, gentamycin-induced nephrotoxic disease control group; gentamycin-induced disease control groups treated with stevia (200 mg/kg/day); amlodipine (4 mg/kg/day); losartan (15 mg/kg/day) and valsartan (5 mg/kg/day) respectively. Fasting blood glucose level and water consumption were recorded daily for the first week and then weekly for the rest of treatment period. Serum creatinine, blood urea, total protein and lipid profile were determined. Histological examination of the heart tissue was assessed to find out any alteration of cardiac muscle tissue following gentamycin-induced nephrotoxicity. This article provides additional data collected from the same animals previously reported [1] .

Thermal transport characterization of carbon and silicon doped stanene nanoribbon: an equilibrium molecular dynamics study.

Equilibrium molecular dynamics simulation has been carried out for the thermal transport characterization of nanometer sized carbon and silicon doped stanene nanoribbon (STNR). The thermal conduction properties of doped stanene nanostructures are yet to be explored and hence in this study, we have investigated the impact of carbon and silicon doping concentrations as well as doping patterns namely single doping, double doping and edge doping on the thermal conductivity of nanometer sized zigzag STNR. The room temperature thermal conductivities of 15 nm × 4 nm doped zigzag STNR at 2% carbon and silicon doping concentration are computed to be 9.31 ± 0.33 W m-1 K-1 and 7.57 ± 0.48 W m-1 K-1, respectively whereas the thermal conductivity for the pristine STNR of the same dimension is calculated as 1.204 ± 0.21 W m-1 K-1. We find that the thermal conductivity of both carbon and silicon doped STNR increases with the increasing doping concentration for both carbon and silicon doping. The magnitude of increase in STNR thermal conductivity due to carbon doping has been found to be greater than that of silicon doping. Different doping patterns manifest different degrees of change in doped STNR thermal conductivity. Double doping pattern for both carbon and silicon doping induces the largest extent of enhancement in doped STNR thermal conductivity followed by single doping pattern and edge doping pattern respectively. The temperature and width dependence of doped STNR thermal conductivity has also been studied. For a particular doping concentration, the thermal conductivity of both carbon and silicon doped STNR shows a monotonic decaying trend at elevated temperatures while an opposite pattern is observed for width variation i.e. thermal conductivity increases with the increase in ribbon width. Such comprehensive study on doped stanene would encourage further investigation on the proper optimization of thermal transport characteristics of stanene nanostructures and provide deep insight in realizing the potential application of doped STNR in thermoelectric as well as thermal management of stanene based nanoelectronic devices.

Smartphone adapters for digital photomicrography.

BACKGROUND: Photomicrographs in Anatomic Pathology provide a means of quickly sharing information from a glass slide for consultation, education, documentation and publication. While static image acquisition historically involved the use of a permanently mounted camera unit on a microscope, such cameras may be expensive, need to be connected to a computer, and often require proprietary software to acquire and process images. Another novel approach for capturing digital microscopic images is to use smartphones coupled with the eyepiece of a microscope. Recently, several smartphone adapters have emerged that allow users to attach mobile phones to the microscope. The aim of this study was to test the utility of these various smartphone adapters. MATERIALS AND METHODS: We surveyed the market for adapters to attach smartphones to the ocular lens of a conventional light microscope. Three adapters (Magnifi, Skylight and Snapzoom) were tested. We assessed the designs of these adapters and their effectiveness at acquiring static microscopic digital images. RESULTS: All adapters facilitated the acquisition of digital microscopic images with a smartphone. The optimal adapter was dependent on the type of phone used. The Magnifi adapters for iPhone were incompatible when using a protective case. The Snapzoom adapter was easiest to use with iPhones and other smartphones even with protective cases. CONCLUSIONS: Smartphone adapters are inexpensive and easy to use for acquiring digital microscopic images. However, they require some adjustment by the user in order to optimize focus and obtain good quality images. Smartphone microscope adapters provide an economically feasible method of acquiring and sharing digital pathology photomicrographs.

Analgesic and anti-inflammatory activities of leaf extract of Mallotus repandus (Willd.) Muell. Arg.

In folk medicine Mallotus repandus (Willd.) Muell. Arg. is used to treat muscle pain, itching, fever, rheumatic arthritis, snake bite, hepatitis, and liver cirrhosis. This study aimed to evaluate the antinociceptive as well as the anti-inflammatory activities of the methanol extract of leaf. The leaves were extracted with methanol following hot extraction and tested for the presence of phytochemical constituents. Analgesic and anti-inflammatory activities were evaluated using acetic acid induced writhing test, xylene induced ear edema, cotton pellet induced granuloma, and tail immersion methods at doses of 500, 1000, and 2000 mg/kg body weight. The presence of flavonoids, saponins, and tannins was identified in the extract. The extract exhibited considerable antinociceptive and anti-inflammatory activities against four classical models of pain. In acetic acid induced writhing, xylene induced ear edema, and cotton pellet granuloma models, the extract revealed dose dependent activity. Additionally, it increased latency time in tail immersion model. It can be concluded that M. repandus possesses significant antinociceptive potential. These findings suggest that this plant can be used as a potential source of new antinociceptive and anti-inflammatory candidates. The activity of methanol extract is most likely mediated through central and peripheral inhibitory mechanisms. This study justified the traditional use of leaf part of this plant.

Endovascular stenting for carotid artery stenosis: results of local experience at Aga Khan University Hospital, Karachi.

OBJECTIVE: To evaluate the results, complications and initial follow-up of patients after percutaneous stent placement for carotid artery disease. METHODS: A retrospective study was carried out on patients treated with carotid artery stenting at the Radiology Department of Aga Khan University Hospital, Karachi, from September 2002 to December 2005. The patients were selected according to the institutional guidelines for Carotid Angioplasty and stenting. Preliminary angiogram was performed in all patients followed by stent deployment. Distal protection device was used in 12 patients. All patients underwent pre and post procedure independent neurological examinations. Follow-up consisted of serial duplex ultrasonography and clinical assessment. RESULTS: Total of 18 stentings were carried out on 17 patients, with one patient having bilateral carotid stenting. There were 14 males and 3 females with an age range of 13 to 68 years. Technical success rate of stent deployment was 100%. Two patients developed Transient Ischaemic Attack (TIA) with transient monoparesis. One patient had confusion and TIA (Hemiparesis) during the preliminary angiogram before stenting. One patient acquired asystole during the procedure; however, he recovered with resuscitation. Five patients had transient bradycardia and hypotension. All these patients recovered with conservative therapy. No stroke or death occurred in any of our patients who underwent this procedure. CONCLUSION: The initial experience revealed satisfactory results with low morbidity rate.