Synthesis, Characterization, Applications and Computational Studies of Nanomaterials

A special issue of Crystals (ISSN 2073-4352). This special issue belongs to the section "Inorganic Crystalline Materials".

Deadline for manuscript submissions: closed (26 April 2024) | Viewed by 3810

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Department of Soil and Environmental Sciences, National Chung Hsing University, Taichung 40227, Taiwan
Interests: plant bioactive compounds; plant toxins; alkaloids; biological activity; spectroscopy;density functional theory; machine learning; virtual screening
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Special Issue Information

Dear Colleagues,

Advances in the green chemical industry and sustainable energy production depend on the development of novel nanomaterials that can be used as adsorbents, catalysts, sensors, and electrodes. In this Special Issue, many fundamental aspects are discussed, such as pore size, surface area, and ligand functionalization of nanomaterials for adsorption, catalysis, and sensing. Promising energy storage systems are also included, which usually work on the principle of adsorption.

Furthermore, the study of nanomaterials using computational approaches, such as ab initio, DFT, molecular dynamics, Monte Carlo, and machine learning methods, is a rapidly developing field that provides a solid foundation for understanding the structure and functional applications of nanomaterials. This Special Issue, therefore, brings together synthesis, characterization, applied and computational studies of nanomaterials, including experimental and computational results on nanomaterials and original research contributions in the fields of environmental remediation, chemical industry, sensors, biosensors, nano-drug delivery systems (NDDSs), electrochemical energy storage and conversion, etc.

Prof. Dr. Chia Ming Chang
Guest Editor

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Keywords

  • synthesis
  • characterization
  • nanomaterials
  • adsorbents
  • catalysts
  • sensors
  • energy storage materials
  • computational methods

Published Papers (3 papers)

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Research

14 pages, 3337 KiB  
Article
Investigating the Fundamental Conditions for Quantitative Growth to Obtain High-Quality WS2 Using a Process of Physical Vapor Deposition
by Yassine Madoune, Sid Ali Madoune, Luzhi Zhang, Reyadh A. M. Taha, Fuad A. Awwad and Emad A. A. Ismail
Crystals 2023, 13(9), 1373; https://doi.org/10.3390/cryst13091373 - 14 Sep 2023
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Abstract
Two-dimensional layered transition-metal dichalcogenides (2D-TMDs) have garnered significant attention due to their layer number-dependent electronic properties, making them promising candidates for atomically thin electronics and optoelectronics. However, current research has primarily focused on exfoliated TMD materials, which have limitations in size, layer number [...] Read more.
Two-dimensional layered transition-metal dichalcogenides (2D-TMDs) have garnered significant attention due to their layer number-dependent electronic properties, making them promising candidates for atomically thin electronics and optoelectronics. However, current research has primarily focused on exfoliated TMD materials, which have limitations in size, layer number control, and yield. Therefore, a crucial challenge remains in producing large single TMD crystals with precise control over the layer number. A comprehensive understanding and precise control of the growth conditions are imperative to address this challenge. This study systematically investigated key growth conditions, including temperature, precursor flow, growth duration, material quantity, gas flow, and slide position. By optimizing these parameters, we successfully synthesized TMD materials with an impressive size of 850 µm. Notably, we achieved the preparation of monolayer WS2 single crystals on a large scale within a remarkably short duration of 10 min, exhibiting a lateral growth rate of up to 1.4 μm/s, which is comparable to the best-exfoliated monolayers. The findings from our study provide a robust pathway for the rapid growth of high-quality TMD single crystals, facilitating further advancements in this field. Full article
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14 pages, 5946 KiB  
Article
Electrodeposited Fabrication of CeO2 Branched-like Nanostructure Used for Nonenzymatic Glucose Biosensor
by Nguyen Thi Nguyet, Chu Van Tuan, Dang Thi Thuy Ngan, Phuong Dinh Tam, Vinh Dinh Nguyen and Nguyen Trong Nghia
Crystals 2023, 13(9), 1315; https://doi.org/10.3390/cryst13091315 - 29 Aug 2023
Cited by 1 | Viewed by 965
Abstract
The fabrication of nonenzymatic glucose sensors is essential because of the enhancement in the selectivity and accuracy of these sensors. In this work, we used the electrodeposition approach to prepare a CeO2-based electrode for nonenzymatic glucose detection. A CeO2 branched-like [...] Read more.
The fabrication of nonenzymatic glucose sensors is essential because of the enhancement in the selectivity and accuracy of these sensors. In this work, we used the electrodeposition approach to prepare a CeO2-based electrode for nonenzymatic glucose detection. A CeO2 branched-like nanostructure was successfully fabricated by electrodeposition on the surface of a Au substrate electrode at room temperature. The effects of cyclic voltammetry, CH3COOH content, and scan cycle number on the formation of the CeO2 branched-like nanostructure were investigated. The fabricated electrodes were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The results showed that a CeO2 branched-like nanostructure could be obtained with a CH3COOH content of 1.0 mL and a scan cycle number of 100 in a solution containing 0.015 M Ce(NO3)3, 0.01 M KCl, and 0.02 M CH3COONH4 and with a scan rate of 400 mV/s. The electrochemical characteristics of the sensor were examined by chronoamperometry and cyclic voltammetry. The results showed that the sensitivity of the sensor was 37.72 μA/mM·cm2 and the limit of detection (LOD) of the sensor was 0.093 mM. The findings in this work prove that it is feasible to fabricate CeO2-based sensors for nonenzymatic glucose detection. Full article
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13 pages, 1660 KiB  
Article
Quantum Chemical GA-MLR, Cluster Model, and Conceptual DFT Descriptors Studies on the Binding Interaction of Estrogen Receptor Alpha with Endocrine Disrupting Chemicals
by Shu-Chun Chi, Hsing-Cheng Hsi and Chia-Ming Chang
Crystals 2023, 13(2), 228; https://doi.org/10.3390/cryst13020228 - 27 Jan 2023
Viewed by 1271
Abstract
In the present study, the predication of the binding affinity (log RBA) of estrogen receptor alpha with three categories of environmental endocrine disrupting chemicals (EDCs), namely, PCB, phenol, and DDT, is performed by the quantum chemical genetic algorithm multiple linear regression (GA-MLR) method. [...] Read more.
In the present study, the predication of the binding affinity (log RBA) of estrogen receptor alpha with three categories of environmental endocrine disrupting chemicals (EDCs), namely, PCB, phenol, and DDT, is performed by the quantum chemical genetic algorithm multiple linear regression (GA-MLR) method. The result of the optimal model indicates that log RBA increases with increasing the electrophilicity and hydrophobicity of EDCs. However, by using the quantum chemical cluster model approach, the modeling results reveal that electrostatic interaction and hydrogen bonding play a significant role. The chemical reactivity descriptors calculated based on the conceptual density functional theory also indicate that the binding mechanism of charge-controlled interaction is superior to that of frontier-controlled interaction. Full article
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