First-Principles Approach for Assessing the Detection of Alzheimer’s Biomarkers Using Titanium Carbide MXenes

Abstract

Alzheimer's disease (AD) is considered the most common neurodegenerative condition and is the main cause of dementia. AD progresses rapidly and is the major cause of death in the elderly population; thus, an early diagnosis is of vital importance. Medical research has successfully characterized a set of volatile organic compounds (VOCs) present in exhaled patient's breath to be considered as fingerprints of AD. The present work, for the first time, aims at computationally designing highly efficient nano-biosensors capable of detecting the VOC biomarkers. We apply density functional theory (DFT) to study the adsorption properties of three representative VOCs, namely, 2,3-dimethylheptane (23-DMH), butylated hydroxytoluene (BHT), and pivalic acid (PVA), versus four interfering air molecules (i.e., N 2 , O 2 , CO 2 , and H 2 O) on four different MXenes (i.e., thick Ti 3 C 2 T x and thin Ti 2 CT x MXenes, T x = O or S). All the molecules are found to exhibit physisorption interactions on the studied MXenes. Nevertheless, the energetic analysis shows clear selective adsorption of BHT on Ti 3 C 2 O 2 with an adsorption energy of −1.513 eV, which is desirable for practical sensing applications. Furthermore, distinct from all other VOCs and interfering air molecules, BHT oxidizes to the O passivation layer of MXenes with a charge transfer of +0.421e and induces magnetization of 0.467 μ B to transform the surface to become ferromagnetic. These changes are very promising to rectify the current−voltage characteristics and yield a high sensor response. We further performed thermodynamic analysis through the Langmuir adsorption model, which ensures the excellent adsorption performance of Ti 3 C 2 O 2 over a broad range of BHT concentrations at ambient temperature. Therefore, Ti 3 C 2 O 2 could be considered as highly sensitive and selective nano-biosensors toward the fingerprint VOCs of AD.