Density functional theory and phytochemical study of 8-hydroxyisodiospyrin

Ullah, Zakir; Ata-ur-Rahman, Ata-ur-Rahman; Fazl-i-Sattar,; Rauf, Abdur; Muhammad, Yaseen; Hassan, Waseem; Tariq, Muhammad; Ayub, Khurshid; Tahir, Asif Ali; Ullah, Habib

doi:10.1016/j.molstruc.2015.04.027

Cited by 55 publications

(11 citation statements)

References 35 publications

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“…Metal nanoparticles (NPs) are employed as heterogeneous photocatalysts in this method. TiO2 (Gupta et al, 2007;Kansal et al, 2013), ZnO (Ullah et al, 2015), BiVO4 (Chomkitichai et al, 2019), WO3 (Khan, Khan, Usman, Imran, & Saeed, 2020), Fe2O3 (Abhilash, Akshatha, & Srikantaswamy, 2019) and copper-based NPs have all been reported as potential heterogeneous photocatalysts (Gu, Chen, Chen, Zhou, & Parsaee, 2018).…”

Section: Introductionmentioning

confidence: 99%

Simple synthesis of novel Lanthanum doped Copper oxide nanoparticles for wastewater treatment: A comparison between Experiment and COMSOL simulation

Masood

Iqbal

Afsheen

et al. 2022

Preprint

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Photocatalysis is a promsing technique for remediation and decontamination of waste water. This research work focuses on the synthesis of pure and lanthanum (La)- (1, 2 and 3 wt%) doped copper oxide nanoparticles (CuO-NPs) via a simple, cost effective and efficient sol-gel process. Differnet characterization techniques such as UV-vis, PL, SEM, XRD, EDS and FTIR are used to investigate optical, compositonal, structural and morphological properties of the synthesized material. Quite interestingly, doping of rare earth element La has reduced the particle size (52.02 ± 0.04 nm to 42.39 ± 0.02 nm) of CuO-NPs. Additionaly, with doping, the band gap and electron hole recombiantion rate is also reduced. Band gap has shifted towards visible region (3.13 ev to 2.85 ev) which makes it an excellent mateiral for photocataysis. Methylene blue (MB) dye is used as model contamination. Photocatalytic degradation efficieny of 79% is obtained in 150 min by La0.02Cu0.98O against MB under natural light irrradiation. Band gap is increased upon futher doping which attributes to the reduced catalytic efficiency to 73% for La0.03Cu0.97O. Theoratical photocatalytic activity of CuO-NPs against MB dye with particle size of 50nm is carried out using COMSOL Multiphysics 5.3a Licenced version in order to corelate the experimental and theoratical results.

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Section: Introductionmentioning

confidence: 99%

Simple synthesis of novel Lanthanum doped Copper oxide nanoparticles for wastewater treatment: A comparison between Experiment and COMSOL simulation

Masood

Iqbal

Afsheen

et al. 2022

Preprint

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“…To tackle the energy crisis, hydrogen as a renewable, sustainable, and clean fuel has drawn increasing attention in recent years. − Photocatalytic water splitting plays a vital role in the hydrogen evolution. , In order to meet the commercial demand that, the solar to hydrogen conversion efficiency (η STH ) should be at least 10%, and organic polymeric materials are actively investigated due to their easy-to-manipulate properties and variability. , Numerous organic photocatalysts were explored, including graphitic carbon nitride (g-C3N4), , conjugated microporous polymers (CMPs), − covalent organic frameworks, − covalent triazine frameworks, − and linear conjugated polymers. − However, the rational design of linear conjugated polymers has yet to be explored. Hydrogen evolution is inherently related to electronic properties such as ionization potential (IP), electron affinity (EA), and optical bandgap as well as dynamics of exciton generation/separation and charge transport. , With the goal of avoiding tedious synthesis-characterization iterations, the usage of theoretical methods such as density functional theory (DFT) was explored to predict the properties of polymers. − Nevertheless, rapid and accurate identifications of promising conjugated copolymers for hydrogen evolution remain a huge challenge.…”

Section: Introductionmentioning

confidence: 99%

Hydrogen Evolution Prediction for Alternating Conjugated Copolymers Enabled by Machine Learning with Multidimension Fragmentation Descriptors

et al. 2021

ACS Appl. Mater. Interfaces

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Hydrogen evolution by alternating conjugated copolymers has attracted much attention in recent years. To study alternating copolymers with data-driven strategies, two types of multidimension fragmentation descriptors (MDFD), structurebased MDFD (SMDFD), and electronic property-based MDFD (EPMDFD), have been developed with machine learning (ML) algorithms for the first time. The superiority of SMDFD-based models has been demonstrated by the highly accurate and universal predictions of electronic properties. Moreover, EPMDFD-based, experimental-parameter-free ML models were developed for the prediction of the hydrogen evolution reaction, displaying excellent accuracy (real-test accuracy = 0.91). The combination of explainable ML approaches and first-principles calculations was employed to explore photocatalytic dynamics, revealing the importance of electron delocalization in the excited state. Virtual designing of high-performance candidates can also be achieved. Our work illustrates the huge potential of ML-based material design in the field of polymeric photocatalysts toward highperformance photocatalysis.

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“…To avoid the tedious and iterative synthesis-characterization to explore the suitable electronic properties, numerous theoretical calculation methods comprising the density functional theory (DFT) have been adopted to predict the basic polymer properties approaching the experimental parameters [25,26]. However, it is very challenging to achieve desirable predictions rapidly and accurately.…”

Section: Introductionmentioning

confidence: 99%

Electronic Properties and Photocatalytic Hydrogen Evolution Rates for Alternating Conjugated Copolymers: Predictions and Insights by Data-Driven Models

Xu¹,

C²,

B³

et al. 2020

Preprint

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Alternating conjugated copolymers have been regarded as promising candidates for photocatalytic hydrogen evolution due to the adjustability of their molecular structures and electronic properties. In this work, machine learning (ML) models with molecular fingerprint of segment descriptors (SD) have been successfully constructed to promote the accurate and universal prediction of electronic properties such as electron affinity, ionization potential and optical bandgap. Moreover, without any experimental values, a high-performance prediction classifier model toward photocatalytic hydrogen production of alternating copolymers has been developed with high accuracy (real-test accuracy = 0.91). Consequently, our results demonstrate accurate regression and classification models to disclose valuable influencing factors concerning hydrogen evolution rate (HER) of alternating copolymers.

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Density functional theory and phytochemical study of 8-hydroxyisodiospyrin

Cited by 55 publications

References 35 publications

Simple synthesis of novel Lanthanum doped Copper oxide nanoparticles for wastewater treatment: A comparison between Experiment and COMSOL simulation

Simple synthesis of novel Lanthanum doped Copper oxide nanoparticles for wastewater treatment: A comparison between Experiment and COMSOL simulation

Hydrogen Evolution Prediction for Alternating Conjugated Copolymers Enabled by Machine Learning with Multidimension Fragmentation Descriptors

Electronic Properties and Photocatalytic Hydrogen Evolution Rates for Alternating Conjugated Copolymers: Predictions and Insights by Data-Driven Models

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