@article{al2024development,

title = {Development of Poly (safranine-co-phenosafranine)/GNPs/MWCNTs Nanocomposites for Quartz Crystal Microbalance Sensor Detection of Arsenic (III) Ions},

author = {Salsabeel Al-Sodies and Abdullah M Asiri and Sameh Ismail and Khalid A Alamry and Mahmoud Hussein Abdo},

url = {https://iopscience.iop.org/article/10.1088/2053-1591/ad37a5/meta},

year  = {2024},

date = {2024-04-12},

urldate = {2024-04-12},

journal = {Materials Research Express},

abstract = {Contamination of drinking water by heavy metals is extremely dangerous to human health. The formation of a quartz crystal microbalance (QCM) sensor for the rapid and portable detection of harmful heavy metals such as arsenic (As) ions in water samples is detailed in this work. Equimolar ratios of safranine (SF) and phenosafranine (Ph) copolymers (PSF-Ph) were synthesized via a chemical oxidative polymerization approach. The copolymer was modified with multi-wall carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) at different percentages (1, 3, 5, and 10%) to form nanocomposites of PSF-Ph/MWCNTs/GNPs. Thermal analysis of the nanocomposites revealed that the final polymer decomposition temperature (PDTfinal) values fell between 619 and 630 °C, and the nanocomposite with 10% loading exhibited the highest decomposition temperatures for T10, T30, and T50. The nanohybrid QCM sensor detected As(III) down to parts-per-billion levels based on the change in the oscillation frequency. The sensor was tested on water samples spiked with different concentrations of As(III) (0–20 ppb). A strong linear correlation (R2 ≈ 0.99) between the frequency shift and concentration with a low detection limit (0.1 ppb) validated the quantitative detection capability of the sensor. This QCM platform with an optimal recognition ligand is a promising field-deployable tool for on-site arsenic analysis in water.},

keywords = {contamination, Drinking water, GNPs (Graphene Nanoplatelets), MWCNTs (Multi-Walled Carbon Nanotubes), Nanocomposites, openQCM sensors, Poly(phenosafranine), Poly(safranine), QCM, Quartz Crystal Microbalance},

pubstate = {published},

tppubtype = {article}

}

@article{sehit2024computationally,

title = {Computationally Designed Epitope-Mediated Imprinted Polymers versus Conventional Epitope Imprints for the Detection of Human Adenovirus in Water and Human Serum Samples},

author = {Ekin Sehit and Guiyang Yao and Giovanni Battocchio and Rahil Radfar and Jakob Trimpert and Maria A Mroginski and Roderich Süssmuth and Zeynep Altintas},

url = {https://pubs.acs.org/doi/full/10.1021/acssensors.3c02374},

doi = {https://doi.org/10.1021/acssensors.3c02374},

year  = {2024},

date = {2024-03-15},

urldate = {2024-03-15},

journal = {ACS sensors},

publisher = {ACS Publications},

abstract = {Detection of pathogenic viruses for point-of-care applications has attracted great attention since the COVID-19 pandemic. Current virus diagnostic tools are laborious and expensive, while requiring medically trained staff. Although user-friendly and cost-effective biosensors are utilized for virus detection, many of them rely on recognition elements that suffer major drawbacks. Herein, computationally designed epitope-imprinted polymers (eIPs) are conjugated with a portable piezoelectric sensing platform to establish a sensitive and robust biosensor for the human pathogenic adenovirus (HAdV). The template epitope is selected from the knob part of the HAdV capsid, ensuring surface accessibility. Computational simulations are performed to evaluate the conformational stability of the selected epitope. Further, molecular dynamics simulations are executed to investigate the interactions between the epitope and the different functional monomers for the smart design of eIPs. The HAdV epitope is imprinted via the solid-phase synthesis method to produce eIPs using in silico-selected ingredients. The synthetic receptors show a remarkable detection sensitivity (LOD: 102 pfu mL–1) and affinity (dissociation constant (Kd): 6.48 × 10–12 M) for HAdV. Moreover, the computational eIPs lead to around twofold improved binding behavior than the eIPs synthesized with a well-established conventional recipe. The proposed computational strategy holds enormous potential for the intelligent design of ultrasensitive imprinted polymer binders.},

keywords = {Antigens, Drinking water, epitope imprinting, in silico-designed epitope-mediated adenovirus receptors, molecular dynamics, Monomers, openQCM Q-1, QCM, QCM sensor, Receptors, sensors, virus detection},

pubstate = {published},

tppubtype = {article}

}