Displaying publications 1 - 20 of 47 in total

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  1. Fulltext Synthesis, in vitro urease inhibitory potential and molecular docking study of benzofuran-based-thiazoldinone analogues
    Taha M, Rahim F, Ullah H, Wadood A, Farooq RK, Shah SAA, et al.
    Sci Rep, 2020 06 30;10(1):10673.
    PMID: 32606439 DOI: 10.1038/s41598-020-67414-7
    In continuation of our work on enzyme inhibition, the benzofuran-based-thiazoldinone analogues (1-14) were synthesized, characterized by HREI-MS, 1H and 13CNMR and evaluated for urease inhibition. Compounds 1-14 exhibited a varying degree of urease inhibitory activity with IC50 values between 1.2 ± 0.01 to 23.50 ± 0.70 µM when compared with standard drug thiourea having IC50 value 21.40 ± 0.21 µM. Compound 1, 3, 5 and 8 showed significant inhibitory effects with IC50 values 1.2 ± 0.01, 2.20 ± 0.01, 1.40 ± 0.01 and 2.90 ± 0.01 µM respectively, better than the rest of the series. A structure activity relationship (SAR) of this series has been established based on electronic effects and position of different substituents present on phenyl ring. Molecular docking studies were performed to understand the binding interaction of the compounds.
  2. Fulltext Formulation and application of optimal homotopty asymptotic method to coupled differential-difference equations
    Ullah H, Islam S, Khan I, Shafie S, Fiza M
    PLoS One, 2015;10(4):e0120127.
    PMID: 25874457 DOI: 10.1371/journal.pone.0120127
    In this paper we applied a new analytic approximate technique Optimal Homotopy Asymptotic Method (OHAM) for treatment of coupled differential-difference equations (DDEs). To see the efficiency and reliability of the method, we consider Relativistic Toda coupled nonlinear differential-difference equation. It provides us a convenient way to control the convergence of approximate solutions when it is compared with other methods of solution found in the literature. The obtained solutions show that OHAM is effective, simpler, easier and explicit.
  3. Fulltext Bioaccumulation of heavy metals in some commercially important fishes from a tropical river estuary suggests higher potential health risk in children than adults
    Ahmed ASS, Sultana S, Habib A, Ullah H, Musa N, Hossain MB, et al.
    PLoS One, 2019;14(10):e0219336.
    PMID: 31622361 DOI: 10.1371/journal.pone.0219336
    The Karnaphuli River estuary, located in southeast coast of Bangladesh, is largely exposed to heavy metal contamination as it receives a huge amount of untreated industrial effluents from the Chottagram City. This study aimed to assess the concentrations of five heavy metals (As, Pb, Cd, Cr and Cu) and their bioaccumulation status in six commercially important fishes, and also to evaluate the potential human health risk for local consumers. The hierarchy of the measured concentration level (mg/kg) of the metals was as follows: Pb (13.88) > Cu (12.10) > As (4.89) > Cr (3.36) > Cd (0.39). The Fulton's condition factor denoted that fishes were in better 'condition' and most of the species were in positive allometric growth. The bioaccumulation factors (BAFs) of the contaminants observed in the species were in the following orders: Cu (1971.42) > As (1042.93) > Pb (913.66) > Cr (864.99) > Cd (252.03), and among the specimens, demersal fish, Apocryptes bato appeared to be the most bioaccumulative organism. Estimated daily intake (EDI), target hazard quotient (THQ), hazard index (HI) and carcinogenic risk (CR) assessed for potential human health risk implications suggest that the values were within the acceptable threshold for both adults and children. However, calculated CR values indicated that both age groups were not far from the risk, and HI values demonstrated that children were nearly 6 times more susceptible to non-carcinogenic and carcinogenic health effects than adults.
  4. Fulltext The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis
    Singla RK, De R, Efferth T, Mezzetti B, Sahab Uddin M, Sanusi, et al.
    Phytomedicine, 2023 Jan;108:154520.
    PMID: 36334386 DOI: 10.1016/j.phymed.2022.154520
    BACKGROUND: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools.

    METHODS: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST.

    RESULTS AND CONCLUSION: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events.

  5. A hysteresis-free perovskite transistor with exceptional stability through molecular cross-linking and amine-based surface passivation
    Kim HP, Vasilopoulou M, Ullah H, Bibi S, Ximim Gavim AE, Macedo AG, et al.
    Nanoscale, 2020 Apr 14;12(14):7641-7650.
    PMID: 32207472 DOI: 10.1039/c9nr10745b
    Organo-metal halide perovskite field-effect transistors present serious challenges in terms of device stability and hysteresis in the current-voltage characteristics. Migration of ions located at grain boundaries and surface defects in the perovskite film are the main reasons for instability and hysteresis issues. Here, we introduce a perovskite grain molecular cross-linking approach combined with amine-based surface passivation to address these issues. Molecular cross-linking was achieved through hydrogen bond interactions between perovskite halogens and dangling bonds present at grain boundaries and a hydrophobic cross-linker, namely diethyl-(12-phosphonododecyl)phosphonate, added to the precursor solution. With our approach, we obtained smooth and compact perovskite layers composed of tightly bound grains hence significantly suppressing the generation and migration of ions. Moreover, we achieved efficient surface passivation of the perovskite films upon surface treatment with an amine-bearing polymer, namely polyethylenimine ethoxylated. With our synergistic grain and surface passivation approach, we were able to demonstrate the first perovskite transistor with a complete lack of hysteresis and unprecedented stability upon continuous operation under ambient conditions. Added to the merits are its ambipolar transport of opposite carriers with balanced hole and electron mobilities of 4.02 and 3.35 cm2 V-1 s-1, respectively, its high Ion/Ioff ratio >104 and the lowest sub-threshold swing of 267 mV dec-1 reported to date for any perovskite transistor. These remarkable achievements obtained through a cost-effective molecular cross-linking of grains combined with amine-based surface passivation of the perovskite films open a new era and pave the way for the practical application of perovskite transistors in low-cost electronic circuits.
  6. Fulltext Synthesis of Novel Triazinoindole-Based Thiourea Hybrid: A Study on α-Glucosidase Inhibitors and Their Molecular Docking
    Taha M, Alshamrani FJ, Rahim F, Hayat S, Ullah H, Zaman K, et al.
    Molecules, 2019 Oct 23;24(21).
    PMID: 31652777 DOI: 10.3390/molecules24213819
    A new class of triazinoindole-bearing thiosemicarbazides (1-25) was synthesized and evaluated for α-glucosidase inhibitory potential. All synthesized analogs exhibited excellent inhibitory potential, with IC50 values ranging from 1.30 ± 0.01 to 35.80 ± 0.80 µM when compared to standard acarbose (an IC50 value of 38.60 ± 0.20 µM). Among the series, analogs 1 and 23 were found to be the most potent, with IC50 values of 1.30 ± 0.05 and 1.30 ± 0.01 µM, respectively. The structure-activity relationship (SAR) was mainly based upon bringing about different substituents on the phenyl rings. To confirm the binding interactions, a molecular docking study was performed.
  7. Fulltext Multipotent Cholinesterase Inhibitors for the Treatment of Alzheimer's Disease: Synthesis, Biological Analysis and Molecular Docking Study of Benzimidazole-Based Thiazole Derivatives
    Hussain R, Ullah H, Rahim F, Sarfraz M, Taha M, Iqbal R, et al.
    Molecules, 2022 Sep 18;27(18).
    PMID: 36144820 DOI: 10.3390/molecules27186087
    Twenty-four analogues of benzimidazole-based thiazoles (1-24) were synthesized and assessed for their in vitro acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibitory potential. All analogues were found to exhibit good inhibitory potential against cholinesterase enzymes, having IC50 values in the ranges of 0.10 ± 0.05 to 11.10 ± 0.30 µM (for AChE) and 0.20 ± 0.050 µM to 14.20 ± 0.10 µM (for BuChE) as compared to the standard drug Donepezil (IC50 = 2.16 ± 0.12 and 4.5 ± 0.11 µM, respectively). Among the series, analogues 16 and 21 were found to be the most potent inhibitors of AChE and BuChE enzymes. The number (s), types, electron-donating or -withdrawing effects and position of the substituent(s) on the both phenyl rings B & C were the primary determinants of the structure-activity relationship (SAR). In order to understand how the most active derivatives interact with the amino acids in the active site of the enzyme, molecular docking studies were conducted. The results obtained supported the experimental data. Additionally, the structures of all newly synthesized compounds were elucidated by using several spectroscopic methods like 13C-NMR, 1H-NMR and HR EIMS.
  8. Fulltext Synthesis and Characterization of Carbon and Carbon-Nitrogen Doped Black TiO2 Nanomaterials and Their Application in Sonophotocatalytic Remediation of Treated Agro-Industrial Wastewater
    Rahman S, Nawaz R, Khan JA, Ullah H, Irfan M, Glowacz A, et al.
    Materials (Basel), 2021 Oct 18;14(20).
    PMID: 34683764 DOI: 10.3390/ma14206175
    The conventional open ponding system employed for palm oil mill agro-effluent (POME) treatment fails to lower the levels of organic pollutants to the mandatory standard discharge limits. In this work, carbon doped black TiO2 (CB-TiO2) and carbon-nitrogen co-doped black TiO2 (CNB-TiO2) were synthesized via glycerol assisted sol-gel techniques and employed for the remediation of treated palm oil mill effluent (TPOME). Both the samples were anatase phase, with a crystallite size of 11.09-22.18 nm, lower bandgap of 2.06-2.63 eV, superior visible light absorption ability, and a high surface area of 239.99-347.26 m2/g. The performance of CNB-TiO2 was higher (51.48%) compared to only (45.72%) CB-TiO2. Thus, the CNB-TiO2 is employed in sonophotocatalytic reactions. Sonophotocatalytic process based on CNB-TiO2, assisted by hydrogen peroxide (H2O2), and operated at an ultrasonication (US) frequency of 30 kHz and 40 W power under visible light irradiation proved to be the most efficient for chemical oxygen demand (COD) removal. More than 90% of COD was removed within 60 min of sonophotocatalytic reaction, producing the effluent with the COD concentration well below the stipulated permissible limit of 50 mg/L. The electrical energy required per order of magnitude was estimated to be only 177.59 kWh/m3, indicating extreme viability of the proposed process for the remediation of TPOME.
  9. Superior photoelectrocatalytic performance of ternary structural BiVO4/GQD/g-C3N4 heterojunction
    Samsudin MFR, Ullah H, Tahir AA, Li X, Ng YH, Sufian S
    J Colloid Interface Sci, 2021 Mar 15;586:785-796.
    PMID: 33198982 DOI: 10.1016/j.jcis.2020.11.003
    Herein, we performed an encyclopedic analysis on the photoelectrocatalytic hydrogen production of BiVO4/g-C3N4 decorated with reduced graphene oxide (RGO) or graphene quantum dots (GQDs). The differences between RGO and GQDs as an electron mediator was revealed for the first time in the perspective of theoretical DFT analysis and experimental validation. It was found that the incorporation of GQDs as an electron mediator promotes better photoelectrocatalytic hydrogen performance in comparison to the RGO. The addition of GQD can significantly improve the activity by 25.2 and 75.7% in comparison to the BiVO4/RGO/g-C3N4 and binary composite samples, respectively. Correspondingly, the BiVO4/GQD/g-C3N4 attained the highest photocurrent density of 19.2 mA/cm2 with an ABPE of 0.57% without the presence of any sacrificial reagents. This enhancement is stemming from the low photocharge carrier transfer resistance which was further verified via DFT study. The DFT analysis revealed that the BiVO4/GQD/g-C3N4 sample shared their electronic cloud density through orbital hybridization while the BiVO4/RGO/g-C3N4 sample show less mutual sharing. Additionally, the charge redistribution of the GQDs-composite at the heterostructure interface articulates a more stable and stronger heterojunction than the RGO-composite. Notably, this study provides new insights on the effect of different carbonaceous materials (RGO and GQDs) which are often used as an electron mediator to enhance photocatalytic activity.
  10. Corrigendum to "Superior photoelectrocatalytic performance of ternary structural BiVO4/GQD/g-C3N4 heterojunction" [J. Col. Interf. Sci. 586 (2021) 785-796]
    Fakhrul Ridhwan Samsudin M, Ullah H, Tahir AA, Li X, Hau Ng Y, Sufian S
    J Colloid Interface Sci, 2021 Nov 15;602:900.
    PMID: 34088501 DOI: 10.1016/j.jcis.2021.04.096
  11. Fulltext The efficacy of deep learning based LSTM model in forecasting the outbreak of contagious diseases
    Absar N, Uddin N, Khandaker MU, Ullah H
    Infect Dis Model, 2022 Mar;7(1):170-183.
    PMID: 34977438 DOI: 10.1016/j.idm.2021.12.005
    The coronavirus disease that outbreak in 2019 has caused various health issues. According to the WHO, the first positive case was detected in Bangladesh on 7th March 2020, but while writing this paper in June 2021, the total confirmed, recovered, and death cases were 826922, 766266 and 13118, respectively. Due to the emergence of COVID-19 in Bangladesh, the country is facing a major public health crisis. Unfortunately, the country does not have a comprehensive health policy to address this issue. This makes it hard to predict how the pandemic will affect the population. Machine learning techniques can help us detect the disease's spread. To predict the trend, parameters, risks, and to take preventive measure in Bangladesh; this work utilized the Recurrent Neural Networks based Deep Learning methodologies like LongShort-Term Memory. Here, we aim to predict the epidemic's progression for a period of more than a year under various scenarios in Bangladesh. We extracted the data for daily confirmed, recovered, and death cases from March 2020 to August 2021. The obtained Root Mean Square Error (RMSE) values of confirmed, recovered, and death cases indicates that our result is more accurate than other contemporary techniques. This study indicates that the LSTM model could be used effectively in predicting contagious diseases. The obtained results could help in explaining the seriousness of the situation, also mayhelp the authorities to take precautionary steps to control the situation.
  12. Fulltext Potential application of nanotechnology in the treatment, diagnosis, and prevention of schistosomiasis
    Qadeer A, Ullah H, Sohail M, Safi SZ, Rahim A, Saleh TA, et al.
    Front Bioeng Biotechnol, 2022;10:1013354.
    PMID: 36568300 DOI: 10.3389/fbioe.2022.1013354
    Schistosomiasis is one of the neglected tropical diseases that affect millions of people worldwide. Globally, it affects economically poor countries, typically due to a lack of proper sanitation systems, and poor hygiene conditions. Currently, no vaccine is available against schistosomiasis, and the preferred treatment is chemotherapy with the use of praziquantel. It is a common anti-schistosomal drug used against all known species of Schistosoma. To date, current treatment primarily the drug praziquantel has not been effective in treating Schistosoma species in their early stages. The drug of choice offers low bioavailability, water solubility, and fast metabolism. Globally drug resistance has been documented due to overuse of praziquantel, Parasite mutations, poor treatment compliance, co-infection with other strains of parasites, and overall parasitic load. The existing diagnostic methods have very little acceptability and are not readily applied for quick diagnosis. This review aims to summarize the use of nanotechnology in the treatment, diagnosis, and prevention. It also explored safe and effective substitute approaches against parasitosis. At this stage, various nanomaterials are being used in drug delivery systems, diagnostic kits, and vaccine production. Nanotechnology is one of the modern and innovative methods to treat and diagnose several human diseases, particularly those caused by parasite infections. Herein we highlight the current advancement and application of nanotechnological approaches regarding the treatment, diagnosis, and prevention of schistosomiasis.
  13. Fulltext DC-GAN-based synthetic X-ray images augmentation for increasing the performance of EfficientNet for COVID-19 detection
    Shah PM, Ullah H, Ullah R, Shah D, Wang Y, Islam SU, et al.
    Expert Syst, 2021 Oct 19.
    PMID: 34898799 DOI: 10.1111/exsy.12823
    Currently, many deep learning models are being used to classify COVID-19 and normal cases from chest X-rays. However, the available data (X-rays) for COVID-19 is limited to train a robust deep-learning model. Researchers have used data augmentation techniques to tackle this issue by increasing the numbers of samples through flipping, translation, and rotation. However, by adopting this strategy, the model compromises for the learning of high-dimensional features for a given problem. Hence, there are high chances of overfitting. In this paper, we used deep-convolutional generative adversarial networks algorithm to address this issue, which generates synthetic images for all the classes (Normal, Pneumonia, and COVID-19). To validate whether the generated images are accurate, we used the k-mean clustering technique with three clusters (Normal, Pneumonia, and COVID-19). We only selected the X-ray images classified in the correct clusters for training. In this way, we formed a synthetic dataset with three classes. The generated dataset was then fed to The EfficientNetB4 for training. The experiments achieved promising results of 95% in terms of area under the curve (AUC). To validate that our network has learned discriminated features associated with lung in the X-rays, we used the Grad-CAM technique to visualize the underlying pattern, which leads the network to its final decision.
  14. Synthesis of bis-indolylmethanes as new potential inhibitors of β-glucuronidase and their molecular docking studies
    Taha M, Ullah H, Al Muqarrabun LMR, Khan MN, Rahim F, Ahmat N, et al.
    Eur J Med Chem, 2018 Jan 01;143:1757-1767.
    PMID: 29133042 DOI: 10.1016/j.ejmech.2017.10.071
    Thirty-two (32) bis-indolylmethane-hydrazone hybrids 1-32 were synthesized and characterized by 1HNMR, 13CNNMR and HREI-MS. All compounds were evaluated in vitro for β-glucuronidase inhibitory potential. All analogs showed varying degree of β-glucuronidase inhibitory potential ranging from 0.10 ± 0.01 to 48.50 ± 1.10 μM when compared with the standard drug d-saccharic acid-1,4-lactone (IC50 value 48.30 ± 1.20 μM). Derivatives 1-32 showed the highest β-glucuronidase inhibitory potentials which is many folds better than the standard drug d-saccharic acid-1,4-lactone. Further molecular docking study validated the experimental results. It was proposed that bis-indolylmethane may interact with some amino acid residues located within the active site of β-glucuronidase enzyme. This study has culminated in the identification of a new class of potent β-glucuronidase inhibitors.
  15. Green synthesis of copper nanoparticle using ionic liquid-based extraction from Polygonum minus and their applications
    Ullah H, Wilfred CD, Shaharun MS
    Environ Technol, 2019 Dec;40(28):3705-3712.
    PMID: 29873603 DOI: 10.1080/09593330.2018.1485751
    The present work reports the extraction of phenolic compounds from Polygonum minus using ionic liquid as extracting solvent. In this work, 1-Butyl-3-methylimidazolium hydrogen sulfate [BMIM][HSO4] was used for the extraction of bioactive compounds. Accordingly, ionic liquids based microwave-assisted extraction treatment for separating of bioactive compounds from polygonum minus was first performed in the present study. The results obtained in this work have high extraction yield in comparison with conventional solvent. UV/Vis results showed that microwave synthesis was fast, well dispersed and nanosized copper nanoparticle (CuNPs) in comparison with conventional synthesis. CuNPs was characterised by X-Rays diffractometer (XRD), Fourier transform infrared (FTIR), dynamic light scattering (DLS), field emission scanning electron microscopy combined with energy dispersive x-rays (FESEM-EDX), and thermogravimetric analysis (TGA). All the instrumental analyses confirmed the particles were nanosized. Furthermore, the antibacterial activity of as-synthesised CuNPs showed effective inhibitory zone against three different bacteria. The photocatalytic degradation of copper nanoparticles was studied using methylene blue (MB) and methyl orange (MO) dyes under UV light and degraded 99.9% within short time 8 and 7 min.
  16. A comprehensive review on pollution status and associated health risk assessment of human exposure to selected heavy metals in road dust across different cities of the world
    Shahab A, Hui Z, Rad S, Xiao H, Siddique J, Huang LL, et al.
    Environ Geochem Health, 2023 Mar;45(3):585-606.
    PMID: 35347514 DOI: 10.1007/s10653-022-01255-3
    In order to expound on the present situation and potential risk of road dust heavy metals in major cities, a total of 114 literatures mainly over the past two decades, involving more than 5000 sampling sites in 61 cities of 21 countries, were screened through the collection and analysis of research papers. The concentration, sources, distribution, health risk, sample collection, and analytical methods of heavy metal research on road dust in cities around the world are summarized. The results show that Cd, Zn, and Cu in many urban road dusts in the world are higher than the grade II of the Chinese maximum allowable concentration of potentially toxic elements in the soil. Geo-accumulation index values show that Pb > Cd > Zn > Cu had the highest contamination levels. Hazard index assessment indicates Pb and Cr had the highest potential health risk, especially for children in which ingestion was found as the main exposure pathway. Moreover, through comparative analysis, it is found that some pollutants are higher in developed and industrialized cities and transport (53%) followed by industrial emissions (35%) provide the major contributions to the sources of heavy metals.
  17. Fulltext An Automatic Premature Ventricular Contraction Recognition System Based on Imbalanced Dataset and Pre-Trained Residual Network Using Transfer Learning on ECG Signal
    Ullah H, Heyat MBB, Akhtar F, Muaad AY, Ukwuoma CC, Bilal M, et al.
    Diagnostics (Basel), 2022 Dec 28;13(1).
    PMID: 36611379 DOI: 10.3390/diagnostics13010087
    The development of automatic monitoring and diagnosis systems for cardiac patients over the internet has been facilitated by recent advancements in wearable sensor devices from electrocardiographs (ECGs), which need the use of patient-specific approaches. Premature ventricular contraction (PVC) is a common chronic cardiovascular disease that can cause conditions that are potentially fatal. Therefore, for the diagnosis of likely heart failure, precise PVC detection from ECGs is crucial. In the clinical settings, cardiologists typically employ long-term ECGs as a tool to identify PVCs, where a cardiologist must put in a lot of time and effort to appropriately assess the long-term ECGs which is time consuming and cumbersome. By addressing these issues, we have investigated a deep learning method with a pre-trained deep residual network, ResNet-18, to identify PVCs automatically using transfer learning mechanism. Herein, features are extracted by the inner layers of the network automatically compared to hand-crafted feature extraction methods. Transfer learning mechanism handles the difficulties of required large volume of training data for a deep model. The pre-trained model is evaluated on the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia and Institute of Cardiological Technics (INCART) datasets. First, we used the Pan-Tompkins algorithm to segment 44,103 normal and 6423 PVC beats, as well as 106,239 normal and 9987 PVC beats from the MIT-BIH Arrhythmia and IN-CART datasets, respectively. The pre-trained model employed the segmented beats as input after being converted into 2D (two-dimensional) images. The method is optimized with the using of weighted random samples, on-the-fly augmentation, Adam optimizer, and call back feature. The results from the proposed method demonstrate the satisfactory findings without the using of any complex pre-processing and feature extraction technique as well as design complexity of model. Using LOSOCV (leave one subject out cross-validation), the received accuracies on MIT-BIH and INCART are 99.93% and 99.77%, respectively, suppressing the state-of-the-art methods for PVC recognition on unseen data. This demonstrates the efficacy and generalizability of the proposed method on the imbalanced datasets. Due to the absence of device-specific (patient-specific) information at the evaluating stage on the target datasets in this study, the method might be used as a general approach to handle the situations in which ECG signals are obtained from different patients utilizing a variety of smart sensor devices.
  18. Rapid fabrication of oxygen defective α-Fe2O3(110) for enhanced photoelectrochemical activities
    Mohamad Noh MF, Ullah H, Arzaee NA, Ab Halim A, Abdul Rahim MAF, Mohamed NA, et al.
    Dalton Trans, 2020 Sep 14;49(34):12037-12048.
    PMID: 32869793 DOI: 10.1039/d0dt00406e
    Defect engineering is increasingly recognized as a viable strategy for boosting the performance of photoelectrochemical (PEC) water splitting using metal oxide-based photoelectrodes. However, previously developed methods for generating point defects associated with oxygen vacancies are rather time-consuming. Herein, high density oxygen deficient α-Fe2O3 with the dominant (110) crystal plane is developed in a very short timescale of 10 minutes by employing aerosol-assisted chemical vapor deposition and pure nitrogen as a gas carrier. The oxygen-defective film exhibits almost 8 times higher photocurrent density compared to a hematite photoanode with a low concentration of oxygen vacancies which is prepared in purified air. The existence of oxygen vacancies improves light absorption ability, accelerates charge transport in the bulk of films, and promotes charge separation at the electrolyte/semiconductor interface. DFT simulations verify that oxygen-defective hematite has a narrow bandgap, electron-hole trapped centre, and strong adsorption energy of water molecules compared to pristine hematite. This strategy might bring PEC technology another step further towards large-scale fabrication for future commercialization.
  19. Self-healing epoxy coating synthesis by embedment of metal 2-methyl imidazole and acetylacetonate complexes with microcapsules
    Ullah H, Qureshi KS, Khan U, Zaffar M, Yang YJ, Rabat NE, et al.
    Chemosphere, 2021 Dec;285:131492.
    PMID: 34273691 DOI: 10.1016/j.chemosphere.2021.131492
    The restoration of mechanical properties is desired for creating the self-healing coatings with no corrosion capabilities. The encapsulation of epoxy resins is limited by various factors in urea and melamine formaldehyde microcapsules. An improved method was developed, where epoxy resin was encapsulated by individual wrapping of poly(melamine-formaldehyde) and poly(urea-formaldehyde) shell around emulsified epoxy droplets via oil-in-water emulsion polymerization method. The synthesized materials were characterized analytically. The curing of the epoxy was achieved by adding the [Ni/Co(2-MI)6].2NO3 as a latent hardener and iron acetylacetonate [Fe(acac)3] as a latent accelerator. Isothermal and non-isothermal differential scanning calorimetric analysis revealed lower curing temperature (Tonset = 116 °C) and lower activation energies (Ea ≈ 69-75 kJ/mol). The addition of microcapsules and complexes did not adversely alter the flexural strength and flexural modulus of the epoxy coatings. The adhesion strength of neat coating decreased from 6310.8 ± 31 to 4720.9 ± 60 kPa and percent healing increased from 50.83 to 67.45% in the presence of acetylacetonate complex at 10 wt% of microcapsules.
  20. The Application of Graphene and Its Derivatives to Energy Conversion, Storage, and Environmental and Biosensing Devices
    Ali Tahir A, Ullah H, Sudhagar P, Asri Mat Teridi M, Devadoss A, Sundaram S
    Chem Rec, 2016 06;16(3):1591-634.
    PMID: 27230414 DOI: 10.1002/tcr.201500279
    Graphene (GR) and its derivatives are promising materials on the horizon of nanotechnology and material science and have attracted a tremendous amount of research interest in recent years. The unique atom-thick 2D structure with sp(2) hybridization and large specific surface area, high thermal conductivity, superior electron mobility, and chemical stability have made GR and its derivatives extremely attractive components for composite materials for solar energy conversion, energy storage, environmental purification, and biosensor applications. This review gives a brief introduction of GR's unique structure, band structure engineering, physical and chemical properties, and recent energy-related progress of GR-based materials in the fields of energy conversion (e.g., photocatalysis, photoelectrochemical water splitting, CO2 reduction, dye-sensitized and organic solar cells, and photosensitizers in photovoltaic devices) and energy storage (batteries, fuel cells, and supercapacitors). The vast coverage of advancements in environmental applications of GR-based materials for photocatalytic degradation of organic pollutants, gas sensing, and removal of heavy-metal ions is presented. Additionally, the use of graphene composites in the biosensing field is discussed. We conclude the review with remarks on the challenges, prospects, and further development of GR-based materials in the exciting fields of energy, environment, and bioscience.
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