Lokman Uzun

Bio: Lokman Uzun is an academic researcher from Hacettepe University. The author has contributed to research in topics: Adsorption & Molecularly imprinted polymer. The author has an hindex of 34, co-authored 148 publications receiving 4609 citations. Previous affiliations of Lokman Uzun include Linköping University & Istanbul Medeniyet University.

Lysine-promoted colorimetric response of gold nanoparticles: a simple assay for ultrasensitive mercury(II) detection.

Abstract: Although numerous methods have been reported for the analysis of toxic mercury (Hg2+) ions in drinking water, development of simple, rapid, inexpensive, and sensitive sensors still remains a great challenge. Here, we report a simple yet very sensitive colorimetric assay for rapid detection of Hg2+ in water. The colorimetric assay is based on the aggregation of as-prepared citrate-capped gold nanoparticles (AuNPs) in the presence of Hg2+ ions and the positively charged amino acid, lysine. The detection limit of this inexpensive colorimetric assay is 2.9 nM, which is below the limit value (10 nM) defined by the U.S. Environmental Protection Agency in drinkable water. Also, the colorimetric response of citrate-capped AuNPs in the presence of lysine is very selective to the Hg2+. In addition, the colorimetric assay is very fast, and all analyses can be completed within a few minutes.

Colorimetric Sensor Array Based on Gold Nanoparticles and Amino Acids for Identification of Toxic Metal Ions in Water

Abstract: A facile colorimetric sensor array for detection of multiple toxic heavy metal ions (Hg2+, Cd2+, Fe3+, Pb2+, Al3+, Cu2+, and Cr3+) in water is demonstrated using 11-mercaptoundecanoic acid (MUA)-capped gold nanoparticles (AuNPs) and five amino acids (lysine, cysteine, histidine, tyrosine, and arginine). The presence of amino acids (which have functional groups that can form complexes with metal ions and MUA) regulates the aggregation of MUA-capped particles; it can either enhance or diminish the particle aggregation. The combinatorial colorimetric response of all channels of the sensor array (i.e., color change in each of AuNP and amino acid couples) enables naked-eye discrimination of all of the metal ions tested in this study with excellent selectivity.

Molecular imprinting: perspectives and applications

Abstract: Molecular imprinting technology (MIT), often described as a method of making a molecular lock to match a molecular key, is a technique for the creation of molecularly imprinted polymers (MIPs) with tailor-made binding sites complementary to the template molecules in shape, size and functional groups. Owing to their unique features of structure predictability, recognition specificity and application universality, MIPs have found a wide range of applications in various fields. Herein, we propose to comprehensively review the recent advances in molecular imprinting including versatile perspectives and applications, concerning novel preparation technologies and strategies of MIT, and highlight the applications of MIPs. The fundamentals of MIPs involving essential elements, preparation procedures and characterization methods are briefly outlined. Smart MIT for MIPs is especially highlighted including ingenious MIT (surface imprinting, nanoimprinting, etc.), special strategies of MIT (dummy imprinting, segment imprinting, etc.) and stimuli-responsive MIT (single/dual/multi-responsive technology). By virtue of smart MIT, new formatted MIPs gain popularity for versatile applications, including sample pretreatment/chromatographic separation (solid phase extraction, monolithic column chromatography, etc.) and chemical/biological sensing (electrochemical sensing, fluorescence sensing, etc.). Finally, we propose the remaining challenges and future perspectives to accelerate the development of MIT, and to utilize it for further developing versatile MIPs with a wide range of applications (650 references).

Wearable sweat sensors

Abstract: Sweat potentially contains a wealth of physiologically relevant information, but has traditionally been an underutilized resource for non-invasive health monitoring. Recent advances in wearable sweat sensors have overcome many of the historic drawbacks of sweat sensing and such sensors now offer methods of gleaning molecular-level insight into the dynamics of our bodies. Here we review key developments in sweat sensing technology. We highlight the potential value of sweat-based wearable sensors, examine state-of-the-art devices and the requirements of the underlying components, and consider ways to tackle data integrity issues within these systems. We also discuss challenges and opportunities for wearable sweat sensors in the development of personalized healthcare.

The Optoelectronic Nose: Colorimetric and Fluorometric Sensor Arrays.

Abstract: A comprehensive review on the development and state of the art of colorimetric and fluorometric sensor arrays is presented Chemical sensing aims to detect subtle changes in the chemical environment by transforming relevant chemical or physical properties of molecular or ionic species (ie, analytes) into an analytically useful output Optical arrays based on chemoresponsive colorants (dyes and nanoporous pigments) probe the chemical reactivity of analytes, rather than their physical properties (eg, mass) The chemical specificity of the olfactory system does not come from specific receptors for specific analytes (eg, the traditional lock-and-key model of substrate-enzyme interactions), but rather olfaction makes use of pattern recognition of the combined response of several hundred olfactory receptors In a similar fashion, arrays of chemoresponsive colorants provide high-dimensional data from the color or fluorescence changes of the dyes in these arrays as they are exposed to analytes This provides chemical sensing with high sensitivity (often down to parts per billion levels), impressive discrimination among very similar analytes, and exquisite fingerprinting of extremely similar mixtures over a wide range of analyte types, in both the gas and liquid phases Design of both sensor arrays and instrumentation for their analysis are discussed In addition, the various chemometric and statistical analyses of high-dimensional data (including hierarchical cluster analysis (HCA), principal component analysis (PCA), linear discriminant analysis (LDA), support vector machines (SVMs), and artificial neural networks (ANNs)) are presented and critiqued in reference to their use in chemical sensing A variety of applications are also discussed, including personal dosimetry of toxic industrial chemical, detection of explosives or accelerants, quality control of foods and beverages, biosensing intracellularly, identification of bacteria and fungi, and detection of cancer and disease biomarkers