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      Lithium doped graphene as spintronic devices

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          Abstract

          Generating spintronic devices has been a goal for the nano-science. We have used density function theory to determine magnetic phases of single layer and bilayer lithium doped graphene nanoflakes. We have introduced graphene flakes as single molecular magnets, spin on/off switches and spintronic memory devices. To aim this goal, adsorption energies, spin polarizations, electronic gaps, magnetic properties and robustness of spin-polarized states have been studied in the presence of dopants and second layers. We find that for bilayer SMMs with two layers of different sizes the highest occupied molecular orbital and the lowest unoccupied molecular orbital switch between the layers. Based on this switch of molecular orbitals in a bilayer graphene SMM, spin on/off switches and spintronic memory devices could be achievable.

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          Most cited references16

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          Local spin density functional approach to the theory of exchange interactions in ferromagnetic metals and alloys

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            Quantum Computing in Molecular Magnets

            , (2009)
            Shor and Grover demonstrated that a quantum computer can outperform any classical computer in factoring numbers and in searching a database by exploiting the parallelism of quantum mechanics. Whereas Shor's algorithm requires both superposition and entanglement of a many-particle system, the superposition of single-particle quantum states is sufficient for Grover's algorithm. Recently, the latter has been successfully implemented using Rydberg atoms. Here we propose an implementation of Grover's algorithm that uses molecular magnets, which are solid-state systems with a large spin; their spin eigenstates make them natural candidates for single-particle systems. We show theoretically that molecular magnets can be used to build dense and efficient memory devices based on the Grover algorithm. In particular, one single crystal can serve as a storage unit of a dynamic random access memory device. Fast electron spin resonance pulses can be used to decode and read out stored numbers of up to 10^5, with access times as short as 10^{-10} seconds. We show that our proposal should be feasible using the molecular magnets Fe8 and Mn12.
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              A 160-kilobit molecular electronic memory patterned at 10(11) bits per square centimetre.

              The primary metric for gauging progress in the various semiconductor integrated circuit technologies is the spacing, or pitch, between the most closely spaced wires within a dynamic random access memory (DRAM) circuit. Modern DRAM circuits have 140 nm pitch wires and a memory cell size of 0.0408 mum(2). Improving integrated circuit technology will require that these dimensions decrease over time. However, at present a large fraction of the patterning and materials requirements that we expect to need for the construction of new integrated circuit technologies in 2013 have 'no known solution'. Promising ingredients for advances in integrated circuit technology are nanowires, molecular electronics and defect-tolerant architectures, as demonstrated by reports of single devices and small circuits. Methods of extending these approaches to large-scale, high-density circuitry are largely undeveloped. Here we describe a 160,000-bit molecular electronic memory circuit, fabricated at a density of 10(11) bits cm(-2) (pitch 33 nm; memory cell size 0.0011 microm2), that is, roughly analogous to the dimensions of a DRAM circuit projected to be available by 2020. A monolayer of bistable, [2]rotaxane molecules served as the data storage elements. Although the circuit has large numbers of defects, those defects could be readily identified through electronic testing and isolated using software coding. The working bits were then configured to form a fully functional random access memory circuit for storing and retrieving information.
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                Author and article information

                Journal
                10.1039/C5RA27922D
                1512.02431

                Nanophysics
                Nanophysics

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