Browsing by Author "Durmaz, Habibe"

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Citation - WoS: 1
Citation - Scopus: 1
Detection of 2,4-Dinitrotoluene by Metal- Graphene Hybrid Plasmonic Nanoantennas With a Golden Ratio Rectangular Resonator
(Kaunas Univ Technology, 2023) Erturan, Ahmet Murat; Gültekin, Seyfettin Sinan; Durmaz, Habibe
Plasmonic nanoantenna arrays have become increasingly popular for the detection of chemical molecules, biomolecules, viruses, and agents. In this study, our objective was to detect explosive-based 2,4-dinitrotoluene (2,4-DNT) with a metal-graphene hybrid plasmonic rectangular nanoantenna with a golden ratio size formed by choosing two consecutive numbers from the Fibonacci series. The golden rectangular resonator provides nearly perfect absorption without the need for impedance matching calculations and complex optimisation algorithms. In surface enhanced infrared absorption (SEIRA) applications, the internal losses of metallic nanostructures degrade their sensing performance. To improve performance sensitivity, graphene with high electrical conductivity and electrical tunability was used. The spectral fingerprints of 2,4 DNT at 6300 nm, 6580 nm, and 7500 nm were enhanced with a metal-graphene hybrid structure. The biosensor platform introduced, by combining the graphene and nanoantennas with a golden ratio and by adjusting the Fermi energy level of graphene, can be beneficial for highly sensitive tunable biosensors for a broad spectrum to identify the molecular fingerprints of specific biomolecules.
Citation - WoS: 13
Citation - Scopus: 15
Machine Learning-Based Approach for Efficient Prediction of Toxicity of Chemical Gases Using Feature Selection
(Elsevier, 2023) Erturan, Ahmet Murat; Karaduman, Gül; Durmaz, Habibe
Toxic gases can be fatal as they damage many living tissues, especially the nervous and respiratory systems. They can cause permanent damage for many years by harming environmental tissue and living organisms. They can also cause mass deaths when used as chemical weapons. These chemical agents consist of organophosphates, namely ester, amide, or thiol derivatives of phosphorus, phosphonic or phosphinic acids, or can be synthesized independently. In this study, machine learning models were used to predict the toxicity of chemical gases. Toxic and non-toxic gases, consisting of 144 gases, were identified according to the United States Environmental Protection Agency, Occupational Safety and Health Administration, and the Centers for Disease Control and Prevention. Six machine-learning models were used to predict the toxicity of these chemical gases. The per-formance of the models was verified through internal and external validation. The results showed that the model's internal validation accuracy was 86.96% with the Relief-J48 algorithm. The accuracy value of the model was 89.65% with the Bayes Net algorithm for external validation. Our results reveal that identifying the toxicity of existing and potential chemicals is essential for the early detection of these chemicals in nature.
Citation - WoS: 1
Citation - Scopus: 1
Simultaneous Detection of Molecules With the Surface-Enhanced Infrared Absorption Sensor Platform Based on Disk Antennas With Double Spacer
(Taylor & Francis Inc, 2023) Erturan, Ahmet Murat; Durmaz, Habibe; Gültekin, Seyfettin Sinan
Biomolecule detection has become important in many applications such as medical diagnosis, forensic analysis, basic biological studies, and food quality assessment. In particular, the Mid-infrared range offers an important opportunity for biomolecular sensing as it covers the molecular vibrational spectra of vital biochemicals such as Deoxyribonucleic acid, Ribonucleic Acid, and proteins. In this study, a double band absorbing plasmonic nanoantenna array with two gold disk resonators is proposed. The biosensing ability of this structure was investigated using the protein-goat anti-mouse immunoglobulin G model and Polymethyl methacrylate film. The basic structural bonds of protein monolayer, namely Amide-I, Amide-II, and Amide-III showed vibrational signatures at 6010 nm (similar to 1664 cm(-1)), 6496 nm (similar to 1539 cm(-1)), and 6989 nm (similar to 1431 cm(-1)) wavelengths, respectively. In addition, the spectral response of the proposed antenna structure was investigated using a Polymethyl methacrylate film by detecting the C=O and the C-H bonds. The strong dipole moment at C=O showed a strong absorption deep at 5782 nm (similar to 1730 cm(-1)) while the C-H bond has shown a relatively low absorption deep at 3350 nm (similar to 2985 cm(-1)) and 3395 nm (similar to 2946 cm(-1)). Our findings indicate that the double spacer disk configuration detects the spectral signature of the protein monolayer and Polymethyl methacrylate film in each band, simultaneously. The dual-band can be tuned independently by carefully engineering the radii of the double disks without making an effect on the other band. The proposed structure can be used as a characterization tool for identifying unknown complex molecules by simply detecting their spectral fingerprints in each mode of the dual-band, independently. Also, this design strategy can be insight to multi-mode SEIRA platforms, where more complex chemical molecules are needed to be detected or identified in biology, chemistry, and defense areas.