Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userFirst-principles study of high conductance DNA sequencing with carbon nanotube electrodes
159
0
0.0
(
0
)
Added by
Chaitanya Das Pemmaraju Dr
Publication date
2011
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
Rapid and cost-effective DNA sequencing at the single nucleotide level might be achieved by measuring a transverse electronic current as single-stranded DNA is pulled through a nano-sized pore. In order to enhance the electronic coupling between the nucleotides and the electrodes and hence the current signals, we employ a pair of single-walled close-ended (6,6) carbon nanotubes (CNTs) as electrodes. We then investigate the electron transport properties of nucleotides sandwiched between such electrodes by using first-principles quantum transport theory. In particular we consider the extreme case where the separation between the electrodes is the smallest possible that still allows the DNA translocation. The benzene-like ring at the end cap of the CNT can strongly couple with the nucleobases and therefore both reduce conformational fluctuations and significantly improve the conductance. The optimal molecular configurations, at which the nucleotides strongly couple to the CNTs, and which yield the largest transmission, are first identified. Then the electronic structures and the electron transport of these optimal configurations are analyzed. The typical tunneling currents are of the order of 50 nA for voltages up to 1 V. At higher bias, where resonant transport through the molecular states is possible, the current is of the order of several $mu$A. Below 1 V the currents associated to the different nucleotides are consistently distinguishable, with adenine having the largest current, guanine the second-largest, cytosine the third and finally thymine the smallest. We further calculate the transmission coefficient profiles as the nucleotides are dragged along the DNA translocation path and investigate the effects of configurational variations. Based on these results we propose a DNA sequencing protocol combining three possible data analysis strategies.
rate research
Read More
Prompted by recent reports on $sqrt{3} times sqrt{3}$ graphene superlattices with intrinsic inter-valley interactions, we perform first-principles calculations to investigate the electronic properties of periodically nitrogen-doped graphene and carbon nanotube nanostructures. In these structures, nitrogen atoms substitute one-sixth of the carbon atoms in the pristine hexagonal lattices with exact periodicity to form perfect $sqrt{3} times sqrt{3}$ superlattices of graphene and carbon nanotubes. Multiple nanostructures of $sqrt{3} times sqrt{3}$ graphene ribbons and carbon nanotubes are explored, and all configurations show nonmagnetic and metallic behaviors. The transport properties of $sqrt{3} times sqrt{3}$ graphene and carbon nanotube superlattices are calculated utilizing the non-equilibrium Greens function formalism combined with density functional theory. The transmission spectrum through the pristine and $sqrt{3} times sqrt{3}$ armchair carbon nanotube heterostructure shows quantized behavior under certain circumstances.
The determination of a patients DNA sequence can, in principle, reveal an increased risk to fall ill with particular diseases [1,2] and help to design personalized medicine [3]. Moreover, statistical studies and comparison of genomes [4] of a large number of individuals are crucial for the analysis of mutations [5] and hereditary diseases, paving the way to preventive medicine [6]. DNA sequencing is, however, currently still a vastly time-consuming and very expensive task [4], consisting of pre-processing steps, the actual sequencing using the Sanger method, and post-processing in the form of data analysis [7]. Here we propose a new approach that relies on functionalized nanopore-embedded electrodes to achieve an unambiguous distinction of the four nucleic acid bases in the DNA sequencing process. This represents a significant improvement over previously studied designs [8,9] which cannot reliably distinguish all four bases of DNA. The transport properties of the setup investigated by us, employing state-of-the-art density functional theory together with the non-equilibrium Greens Function method, leads to current responses that differ by at least one order of magnitude for different bases and can thus provide a much more robust read-out of the base sequence. The implementation of our proposed setup could thus lead to a viable protocol for rapid DNA sequencing with significant consequences for the future of genome related research in particular and health care in general.
Dielectrophoresis can potentially be used as an efficient trapping tool in the fabrication of molecular devices. For nanoscale objects, however, the Brownian motion poses a challenge. We show that the use of carbon nanotube electrodes makes it possible to apply relatively low trapping voltages and still achieve high enough field gradients for trapping nanoscale objects, e.g., single molecules. We compare the efficiency and other characteristics of dielectrophoresis between carbon nanotube electrodes and lithographically fabricated metallic electrodes, in the case of trapping nanoscale DNA molecules. The results are analyzed using finite element method simulations and reveal information about the frequency dependent polarizability of DNA.
Based on the spin-pumping theory and first-principles calculations, the spin-mixing conductance (SMC) is theoretically studied for Pt/Permalloy (Ni$_{81}$Fe$_{19}$, Py) junctions. We evaluate the SMC for ideally clean Pt/Py junctions and examine the effects of interface randomness. We find that the SMC is generally enhanced in the presence of interface roughness as compared to the ideally clean junctions. Our estimated SMC is in good quantitative agreement with the recent experiment for Pt/Py junctions. We propose possible routes to increase the SMC in Pt/Py junctions by depositing a foreign magnetic metal layer in Pt, offering guidelines for designing the future spintronic devices.
Understanding the magnetic properties of graphenic nanostructures is instrumental in future spintronics applications. These magnetic properties are known to depend crucially on the presence of defects. Here we review our recent theoretical studies using density functional calculations on two types of defects in carbon nanostructures: Substitutional doping with transition metals, and sp$^3$-type defects created by covalent functionalization with organic and inorganic molecules. We focus on such defects because they can be used to create and control magnetism in graphene-based materials. Our main results are summarized as follows: i)Substitutional metal impurities are fully understood using a model based on the hybridization between the $d$ states of the metal atom and the defect levels associated with an unreconstructed D$_{3h}$ carbon vacancy. We identify three different regimes, associated with the occupation of distinct hybridization levels, which determine the magnetic properties obtained with this type of doping; ii) A spin moment of 1.0 $mu_B$ is always induced by chemical functionalization when a molecule chemisorbs on a graphene layer via a single C-C (or other weakly polar) covalent bond. The magnetic coupling between adsorbates shows a key dependence on the sublattice adsorption site. This effect is similar to that of H adsorption, however, with universal character; iii) The spin moment of substitutional metal impurities can be controlled using strain. In particular, we show that although Ni substitutionals are non-magnetic in flat and unstrained graphene, the magnetism of these defects can be activated by applying either uniaxial strain or curvature to the graphene layer. All these results provide key information about formation and control of defect-induced magnetism in graphene and related materials.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
