A Molecular Dynamics Model for Biomedical Sensor Evaluation: Nanoscale Numerical Simulation of an Aluminum-Based Biosensor

TY - GEN

T1 - A Molecular Dynamics Model for Biomedical Sensor Evaluation

T2 - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022

AU - Shahbazi, Fatemeh

AU - Esfahani, Mohammad Nasr

AU - Jabbari, Masoud

AU - Keshmiri, Amir

N1 - Funding Information: *Research supported by the department of mechanical, aerospace, and civil engineering, University of Manchester. Publisher Copyright: © 2022 IEEE.

PY - 2022/9/8

Y1 - 2022/9/8

N2 - Metallic nanostructured-based biosensors provide label-free, multiplexed, and real-time detections of chemical and biological targets. Aluminum-based biosensors are favored in this category, due to their enhanced stability and profitability. Despite the recent advances in nanotechnology and the significant improvement in development of these biosensors, some deficiencies restrict their utilization. Hence a detailed insight into their behavior in different conditions would be crucial, which can be achieved with nanoscale numerical simulation. With this aim, an Aluminum-based biosensor is chosen to be analyzed with the help of all-atom molecular dynamics model (AA-MD), using large-scale atomic/molecular massively parallel simulator (LAMMPS). The surface properties and adsorption process through different flow conditions and various concentration of the target, are investigated in this study. In the future work, the results of this study will be used for developing a predictive model for surface properties of the biosensor. Clinical Relevance - The role of biosensors in clinical applications and early diagnosis is evident. This work provides a model for predicting the binding behavior of the target molecules on the biosensor surface in different conditions. Results demonstrate an increase in the adsorption of ethanol on the biosensor surface of 7% up to 80% with changing the velocity from 0.001

AB - Metallic nanostructured-based biosensors provide label-free, multiplexed, and real-time detections of chemical and biological targets. Aluminum-based biosensors are favored in this category, due to their enhanced stability and profitability. Despite the recent advances in nanotechnology and the significant improvement in development of these biosensors, some deficiencies restrict their utilization. Hence a detailed insight into their behavior in different conditions would be crucial, which can be achieved with nanoscale numerical simulation. With this aim, an Aluminum-based biosensor is chosen to be analyzed with the help of all-atom molecular dynamics model (AA-MD), using large-scale atomic/molecular massively parallel simulator (LAMMPS). The surface properties and adsorption process through different flow conditions and various concentration of the target, are investigated in this study. In the future work, the results of this study will be used for developing a predictive model for surface properties of the biosensor. Clinical Relevance - The role of biosensors in clinical applications and early diagnosis is evident. This work provides a model for predicting the binding behavior of the target molecules on the biosensor surface in different conditions. Results demonstrate an increase in the adsorption of ethanol on the biosensor surface of 7% up to 80% with changing the velocity from 0.001

KW - Aluminum

KW - Biosensing Techniques/methods

KW - Molecular Dynamics Simulation

KW - Nanostructures/chemistry

KW - Nanotechnology

UR - http://www.scopus.com/inward/record.url?scp=85138126846&partnerID=8YFLogxK

U2 - 10.1109/EMBC48229.2022.9871498

DO - 10.1109/EMBC48229.2022.9871498

M3 - Conference contribution

C2 - 36086108

VL - 2022

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 613

EP - 616

BT - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 11 July 2022 through 15 July 2022

ER -