Size and Shape Effect of Gold Nanoparticles in “Far‐Field” Surface Plasmon Resonance

Zhuang, Yiqi; Liu, Linlin; Wu, Xiaoyan; Tian, Yu; Zhou, Xuehong; Xu, Shuping; Xie, Zengqi; Ma, Yan

doi:10.1002/ppsc.201800077

Cited by 41 publications

(26 citation statements)

References 35 publications

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“…Figure 1 depicts the UV-Vis spectra of synthesized colloidal GNPs in different volumetric ratios of ethanol to water solvent mixture. Typically, maximum SPR absorption wavelength (λ m ) of GNPs is size and shape dependent [26,27]. As shown in Fig.…”

Section: Transmission Electron Microscopy (Tem) and Particle Size Dismentioning

confidence: 99%

Synthesis of Various Size Gold Nanoparticles by Chemical Reduction Method with Different Solvent Polarity

et al. 2020

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Complicated and strict protocols are followed to tune the size of gold nanoparticles (GNPs) in chemical synthesis methods. In this study, we address the polarity of solvents as a tool for tailoring the size of GNPs in the chemical reduction method. The effects of varying polarity index of the reaction medium on synthesizing gold nanoparticles by chemical reduction method have been investigated. Ethanol as a polar solvent, ethanol-water mixture as reaction medium, L-ascorbic acid as reducing agent, and polyvinylpyrrolidone as stabilizer were used to synthesize GNPs. The polarity index of the reaction medium was adjusted by changing the volume ratio of ethanol to water. UV-Vis, dynamic light scattering (DLS), and transmission electron microscopy (TEM) characterizations reveal that the growth of nanoparticles was gradually increased (~22 to 219 nm hydrodynamic diameter) with decreasing value of polarity index of the reaction medium (~8.2 to 5.2). Furthermore, the high polarity index of the reaction medium produced smaller and spherical nanoparticles, whereas lower polarity index of reaction medium results in bigger size of GNPs with different shapes. These results imply that the mechanistic of the growth, assembly, and aggregation phenomena of ligand or stabilizer-capped GNPs strongly rely on the polarity of solvent molecules. Using the proposed methodology, wide size range of GNPs with different morphology sizes can be synthesized by simply modulating the volume percentage of organic solvent in the reaction medium.

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Section: Transmission Electron Microscopy (Tem) and Particle Size Dismentioning

confidence: 99%

Synthesis of Various Size Gold Nanoparticles by Chemical Reduction Method with Different Solvent Polarity

et al. 2020

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“…The first enhancement maximum is located at around 5–10 nm; with the continued increase of the distance, the second fluorescence enhancement occurs at around 80–120 nm. The first enhancement is due to the LSPR effect as discussed above, which asks for the overlapping of the emission peak of fluorescent molecules and the absorption peak of metal NPs . The second enhancement is ascribed to the FSPR effect, as a result of the reflection of light on the surface of the metal NPs.…”

Section: The Properties Of Metal‐containing Nanomaterialsmentioning

confidence: 94%

“…The first enhancement is due to the LSPR effect as discussed above, which asks for the overlapping of the emission peak of fluorescent molecules and the absorption peak of metal NPs. [68] The second enhancement is ascribed to the FSPR effect, as a result of the reflection of light on the surface of the metal NPs. Specifically, the reflected light interacts with the emitted light to cause a change in the effective dielectric constant, which is manifested by the increase of the radiative transition rate and fluorescence quantum yield.…”

Section: Fspr Effect Of Metallic Nanomaterialsmentioning

confidence: 99%

Recent Advances in the Optimization of Organic Light‐Emitting Diodes with Metal‐Containing Nanomaterials

Lian

Shen

Guo

et al. 2019

The Chemical Record

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Metal-containing nanomaterials have attracted widespread attention in recent years due to their physicochemical, light-scattering and plasmonic properties. By introducing different kinds and different structures of metal-containing nanomaterials into organic light-emitting diodes (OLEDs), the optical properties of the devices can be tailored, which can effectively improve the luminous efficiency of OLEDs. In this review, the fundamental knowledge of OLEDs and metallic nanomaterials were firstly introduced. Then we overviewed the recent development of the optimization of OLEDs through introducing different kinds of metalcontaining nanomaterials.to now, many review papers have been published mainly focusing on the development of organic functional materials and device structures of OLEDs, however, there is still no comprehensive overview on the optimization of OLEDs with the metal-containing nanomaterials, which is very attractive for both academic research and commercial application of high performance OLEDs and other optoelectronic devices. [37][38][39][40][41][42] In this review, the fundamental knowledge of OLEDs and metallic nanomaterials were firstly introduced. Then we overviewed the recent development of the optimization of OLEDs through introducing different kinds of metal-containing nanomaterials. 2 3 4 5 6 7 8

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“…However, they proposed that more in-depth investigations under different temperatures and gases (oxidizing/reducing) are required to understand the effect of defects on gas sensing [45,74]. Tuning of the surface energy and altering the band gap both can be vital for providing active sites to gas molecules [32,[75][76][77][78]. Therefore, considerable research works are conducted to develop and explore various micro-(from thick film to highly porous 3D hierarchical structure) and nanostructures (nanoparticles (NPs), nanorods (NRs), nanotube (NTs), nanowires (NWs), and nanocapsules (NCps), etc.)…”

Section: Chemical Gas Sensors: Achievements and Challengesmentioning

confidence: 99%

Chemical Gas Sensors: Recent Developments, Challenges, and the Potential of Machine Learning—A Review

Yaqoob

Younis

2021

Sensors

150

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Nowadays, there is increasing interest in fast, accurate, and highly sensitive smart gas sensors with excellent selectivity boosted by the high demand for environmental safety and healthcare applications. Significant research has been conducted to develop sensors based on novel highly sensitive and selective materials. Computational and experimental studies have been explored in order to identify the key factors in providing the maximum active location for gas molecule adsorption including bandgap tuning through nanostructures, metal/metal oxide catalytic reactions, and nano junction formations. However, there are still great challenges, specifically in terms of selectivity, which raises the need for combining interdisciplinary fields to build smarter and high-performance gas/chemical sensing devices. This review discusses current major gas sensing performance-enhancing methods, their advantages, and limitations, especially in terms of selectivity and long-term stability. The discussion then establishes a case for the use of smart machine learning techniques, which offer effective data processing approaches, for the development of highly selective smart gas sensors. We highlight the effectiveness of static, dynamic, and frequency domain feature extraction techniques. Additionally, cross-validation methods are also covered; in particular, the manipulation of the k-fold cross-validation is discussed to accurately train a model according to the available datasets. We summarize different chemresistive and FET gas sensors and highlight their shortcomings, and then propose the potential of machine learning as a possible and feasible option. The review concludes that machine learning can be very promising in terms of building the future generation of smart, sensitive, and selective sensors.

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Size and Shape Effect of Gold Nanoparticles in “Far‐Field” Surface Plasmon Resonance

Cited by 41 publications

References 35 publications

Synthesis of Various Size Gold Nanoparticles by Chemical Reduction Method with Different Solvent Polarity

Synthesis of Various Size Gold Nanoparticles by Chemical Reduction Method with Different Solvent Polarity

Recent Advances in the Optimization of Organic Light‐Emitting Diodes with Metal‐Containing Nanomaterials

Chemical Gas Sensors: Recent Developments, Challenges, and the Potential of Machine Learning—A Review

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