Organic vapor sensing properties of copolymer Langmuir-Blodgett thin film sensors

Açıkbaş, Yaser; Doğan, Gamze; Erdoğan, Matem; Çapan, Rıfat; Soykan, Cengiz

doi:10.1080/10601325.2016.1189279

Cited by 16 publications

(6 citation statements)

References 15 publications

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“…However, such a behavior of the sensors can be explained by the interaction between the chemical structure of the material and the organic vapor. It is well-known that the H-bonding ability, π–π interaction, host–guest interaction, and physical parameters of VOCs play an important role in the vapor sensing process between organic thin film materials and VOC vapors. − Because the electronic cage of P[5]-1 is more appropriate, it easily captures the VOC molecules with the molecular interaction principle. In particular, the nitrogens on the multitriazole units enable an excellent hydrogen bonding interaction between macroring and VOCs. − When the diameter of pillar[5]arene after bounded triazole fragments is compared with the diameter of the pillar[5]arene, including azide moieties, P[5]-1 has a larger cavity that is ideally suited for larger solvents.…”

Section: Resultsmentioning

confidence: 99%

Sensing Volatile Pollutants with Spin-Coated Films Made of Pillar[5]arene Derivatives and Data Validation via Artificial Neural Networks

Kursunlu,

Acikbas,

Yilmaz

et al. 2024

ACS Appl. Mater. Interfaces

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Different types of solvents, aromatic and aliphatic, are used in many industrial sectors, and long-term exposure to these solvents can lead to many occupational diseases. Therefore, it is of great importance to detect volatile organic compounds (VOCs) using economic and ergonomic techniques. In this study, two macromolecules based on pillar[5]arene, named P[5]-1 and P[5]-2, were synthesized and applied to the detection of six different environmentally volatile pollutants in industry and laboratories. The thin films of the synthesized macrocycles were coated by using the spin coating technique on a suitable substrate under optimum conditions. All compounds and the prepared thin film surfaces were characterized by NMR, Fourier transform infrared (FT-IR), elemental analysis, atomic force microscopy (AFM), scanning electron microscopy (SEM), and contact angle measurements. All vapor sensing measurements were performed via the surface plasmon resonance (SPR) optical technique, and the responses of the P[5]-1 and P[5]-2 thin-film sensors were calculated with ΔI/I o × 100. The responses of the P[5]-1 and P[5]-2 thin-film sensors to dichloromethane vapor were determined to be 7.17 and 4.11, respectively, while the responses to chloroform vapor were calculated to be 5.24 and 2.8, respectively. As a result, these thin-film sensors showed a higher response to dichloromethane and chloroform vapors than to other harmful vapors. The SPR kinetic data for vapors validated that a nonlinear autoregressive neural network was performed with exogenous input for the best molecular modeling by using normalized reflected light intensity values. It can be clearly seen from the correlation coefficient values that the nonlinear autoregressive with exogenous input artificial neural network (NARX-ANN) model for dichloromethane converged more successfully to the experimental data compared to other gases. The correlation coefficient values of the dichloromethane modeling results were approximately 0.99 and 0.98 for P[5]-1 and P[5]-2 thin-film sensors, respectively.

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Section: Resultsmentioning

confidence: 99%

Sensing Volatile Pollutants with Spin-Coated Films Made of Pillar[5]arene Derivatives and Data Validation via Artificial Neural Networks

Kursunlu,

Acikbas,

Yilmaz

et al. 2024

ACS Appl. Mater. Interfaces

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“…The surface pressure (26 mN m -1 ) fixed stable by utilizing the movable barrier (under the certain deposition conditions) to obtain the deposition graph of SB77 monolayer film from surface to solid substrate up to four layers (Figure 3). This graph displays that the each layer was successfully transferred by considering and calculating of the transfer ratio for deposited layers [15,16]. It can be estimated that SB 77 is a preferable macrocyclic materials for the fabrication of organized LB thin films from the high value (calculated as ≥ 91%) of transfer ratio.…”

Section: The Process Of Sb77 Lb Thin Film Fabrication and Characterizationmentioning

confidence: 98%

Aromatik hidrokarbonların dedekte edilmesi için kaliksaren bazlı diamid kimyasal sensor çiplerinin geliştirilmesi

Zeybek

Açıkbaş

Bozkurt

et al. 2021

Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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In the present work, a new macrocycle materials (SB77) was selected and Langmuir-Blodgett thin films of this macrocycle compounds were examined for its vapor sensing capabilities against vapor of aromatic BTX hydrocarbons (benzene, toluene, xylene) through Quartz Crystal Microbalance (QCM) technique. In accordance with this aim, the calix [4]arene LB thin films were prepared onto quartz crystal substrates. The characterization of SB77 LB thin film was performed for nine LB layers fabricated onto the quartz crystal. The frequency shifts and the mass changes for monolayer of these LB thin films were obtained as 32.35 Hz / per layer and 2206.65 ng (8.32 ng mm -2 ), respectively. All QCM results indicated that SB77 LB thin film chemical sensors exhibits high response, a good sensitivity and selectivity for benzene vapor at saturated or different concentrations than other aromatic hydrocarbon vapors. These LB thin film sensors with SB77 calix [4]arene macrocycle materials have been potential candidates for organic vapor sensing applications with simple and low cost preparation at room temperature.

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“…In the detection of volatile organic compounds (VOCs), these unique polymers are utilized in the production of sensitive, fast responding, reversible thin film chemicals sensor elements. The main objective of this study is to investigate monomers that can best interact with the volatile organic compounds to be detected and enable the production of efficient chemical sensors [22][23][24]. It is important to synthesize raw materials that are suitable for the molar volume of the gas to be detected and that can form dipole moments or other secondary interactions with the gas.…”

Section: Introductionmentioning

confidence: 99%

Surface plasmon resonance chemical sensor modified with α-naphthylmethacrylate nano thin film for chloroform detection

Acikbas

2023

Res. Eng. Struct. Mat.

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The research on the rapid and sensitive detection of pollution caused by the products and technologies used has recently attracted attention in the literature. In the detection of volatile organic compounds (VOCs), polymers/monomers are used in the production of sensitive, fast-responding, reversible thin-film gas sensor elements. In this work, the monomer α-Naphthylmethacrylate was selected as thin film sensor element. The α-Naphthylmethacrylate-based nano thin films were prepared with technique of LB. Monomer LB thin films fabricated onto gold-coated glass substrate to investigate their vapour sensing properties by using Surface Plasmon Resonance (SPR) optical technique. This prepared monomer-based thin film sensor exposed to five different concentrations of chloroform vapors varying between 13.98x103-69.9x103 ppm and the sensor response values were recorded. Swelling dynamics’ of this monomer thin film sensor was also illuminated by using Fick's early-time diffusion law. Diffusion coefficients of α-Naphthylmethacrylate LB thin film sensor materials exposed to the five different concentrations of chloroform vapor were calculated with the help of reflected light intensity graph data and Fick's Law as a function of time. It was determined that the diffusion coefficient values of the first and second slope regions as varying between 5.72x10-17-21.97x10-17 cm2s-1 and 3.06x10-17-6.25x10-17 cm2s-1, respectively. SPR kinetic measurement results showed that α-Naphthylmethacrylate material is promising for the detection of chloroform vapor.

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Organic vapor sensing properties of copolymer Langmuir-Blodgett thin film sensors

Cited by 16 publications

References 15 publications

Sensing Volatile Pollutants with Spin-Coated Films Made of Pillar[5]arene Derivatives and Data Validation via Artificial Neural Networks

Sensing Volatile Pollutants with Spin-Coated Films Made of Pillar[5]arene Derivatives and Data Validation via Artificial Neural Networks

Aromatik hidrokarbonların dedekte edilmesi için kaliksaren bazlı diamid kimyasal sensor çiplerinin geliştirilmesi

Surface plasmon resonance chemical sensor modified with α-naphthylmethacrylate nano thin film for chloroform detection

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