journal article·2024-02-13Open access

Nanoparticle-Assisted Liquid Crystal Droplet Sensors Enable Analysis of Low-Concentration Species in Aqueous Medium

Selda Sezer, Emre Bukusoglu

Langmuir· Volume 40· Issue 6

Abstract

We introduce nanoparticle-assisted liquid crystal (LC) droplet-based sensors that allow determination of low-level concentrations of aqueous soluble species. The silica nanoparticles functionalized with mixed monolayers composed of two distinct groups, hydrophobic alkane tail- and charged group-terminated silanes, facilitated ternary physical interactions between the model analytes (methylene blue (MB) or methyl orange (MO)) and the nematic mesogens 5CB (4-cyano-4'-pentylbiphenyl), and the interfacial species of the nanoparticle. The response of the LC droplets was measured upon nanoparticle adsorption as a function of analyte concentration, which was characterized by the optical determination of the configuration distributions of the LC droplets. We highlight the importance of the charging and the composition of the nanoparticle interfaces for analytical purposes that allow accurate determination of the concentration of the analytes on the order of 0.01 ppb. Such a low concentration corresponds to a low interfacial coverage of nanoparticles, indicating the promisingly high sensitivity of the sensor platform to target analytes. Distinct from the past examples of the LC-based sensors, the nanoparticle-assisted LC sensors allow detection of the species that do not directly cause an ordering transition at the LC-water interfaces, which allow a broader range of analytical targets. The sensor platform that we report herein can be easily tunable for a range of target molecules and will find use in the determination of a wide range of micropollutants in aqueous environments.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Liquid Crystal Research Advancements · Innovative Microfluidic and Catalytic Techniques Innovation · Microfluidic and Capillary Electrophoresis Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Chemical Engineering, Middle East Technical University, Dumlupinar Bulvari No. 1, Cankaya, Ankara 06800, Turkey

Akcadag Vocational School, Laboratory and Veterinary Health Program, Malatya Turgut Ozal University, Dogu Mahallesi No: 42/1, Akcadag, Malatya 44600, Turkey

Funding

T?rkiye Bilimsel ve Teknolojik Arastirma Kurumu

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