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Author Almabadi, M.H.; Truta, F.M.; Adamu, G.; Cowen, T.; Tertis, M.; Alanazi, K.D.M.; Stefan, M.-G.; Piletska, E.; Kiss, B.; Cristea, C.; De Wael, K.; Piletsky, S.A.; Cruz, A.G. url  doi
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  Title Integration of smart nanomaterials for highly selective disposable sensors and their forensic applications in amphetamine determination Type A1 Journal article
  Year (down) 2023 Publication Electrochimica acta Abbreviated Journal  
  Volume 446 Issue Pages 142009-142010  
  Keywords A1 Journal article; Antwerp Electrochemical and Analytical Sciences Lab (A-Sense Lab)  
  Abstract Screening drugs on the street and biological samples pose a challenge to law enforcement agencies due to existing detection methods and instrument limitations. Herein we present a graphene-assisted molecularly imprinted polymer nanoparticle-based sensor for amphetamine. These nanoparticles are electroactive by incorporating ferrocene in their structure. These particles act as specific actuators in electrochemical sensors, and the presence of a ferrocene redox probe embedded in the structure allows the detection of non-electroactive amphetamine. In a control approach, nanoparticles were covalently immobilised onto electrochemical sensors by drop-casting using silanes. Alternatively, nanoparticles were immobilised employing 3D printing and a graphene ink composite. The electrochemical performance of both approaches was evaluated. As a result, 3D printed nanoMIPs/graphene sensors displayed the highest selectivity in spiked human plasma, with sensitivity at 73 nA nM-1, LOD of 68 nM (RSD 2.4%) when compared to the silane drop cast electrodes. The main advantage of the optimised 3D printing technology is that it allows quantitative determination of amphetamine, a nonelectroactive drug, challenging to detect with conventional electrochemical sensors. In addition, the costefficient 3D printing method makes these sensors easy to manufacture, leading to robust, highly selective and sensitive sensors. As proof of concept, sensors were evaluated on the street specimens and clinically relevant samples and successfully validated using UPLC-MS.  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos 000953087600001 Publication Date 2023-02-09  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0013-4686 ISBN Additional Links UA library record; WoS full record; WoS citing articles  
  Impact Factor 6.6 Times cited Open Access OpenAccess  
  Notes Approved Most recent IF: 6.6; 2023 IF: 4.798  
  Call Number UA @ admin @ c:irua:196145 Serial 8888  
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