Abstract
Background: A metal oxide semiconductor field effect transistor (MOSFET) is widely used to make integrated circuits (ICs). MOSFET devices are reaching the practical limitations for further scaling in the nanoscale regime. It motivates the researchers to explore and develop new ways to advance the electronics industry. Quantum-dot cellular automata (QCA) is a potential way to replace the MOSFET devices in the nanoscale regime. QCA nanotechnology not only solves the issue of scalability but also degrades the leakage current. It has numerous benefits, such as a highly dense design, fast speed, and energy efficiency compared to complementary metal-oxide-semiconductor (CMOS) technology.
Objective: An extensive study of QCA nanotechnology is needed to quickly understand the field. Optimizing the QCA designs is the mandatory requirement to minimize the occupied cell area, latency and quantum cost. The preliminary knowledge of QCA nanotechnology boosts the idea of generating different logic functions. This review paper presents the methodology for making the fundamental logic gates using QCA nanotechnology. XOR gate is commonly used to implement popular circuits such as adders, subtractors, comparators, code converters, reversible gates etc. The various available QCA-based 2-input XOR gate designs are discussed and compared for the different performance metrics.
Methods: Columbic interaction causes logical operations, and data is transferred from one cell to another cell using cell-to-cell interaction. A specific arrangement of QCA cells produces a specific logic. QCA Designer tool using a Bi-stable simulation engine is used to design different digital circuits.
Results: This review paper deals with the design of the 2-input XOR gate. The considered performance metrics for the comparison purpose are cell count, occupied area, clock cycle, and quantum cost. Existing works on 2-input XOR gates show that a minimum of 8 QCA cells are needed for a 2-input XOR gate using QCA nanotechnology. A single clock cycle-based 2-input XOR gate requires at least 9 QCA cells. The quantum cost can be minimized by reducing the number of QCA cells and clock cycles.
Conclusion: This review paper helps the circuit designers to select the appropriate 2-input XOR gate for the design of complex circuits. Circuit designers can use the fundamental concepts detailed in the paper to implement any Boolean function and optimize it for the existing designs. A researcher had developed a 2-input XOR gate using only 8 QCA cells with 0.50 clock cycles. Therefore, designers can start from here to further optimize the 2-input XOR gate with a single clock cycle.
Keywords: Quantum-dot, Nanostructured, XOR, QCA Designer, Cell-to-cell interaction, MV.
[http://dx.doi.org/10.1109/TED.2017.2756106]
[http://dx.doi.org/10.1109/JPROC.2010.2068030]
[http://dx.doi.org/10.1109/JPROC.2010.2064272]
[http://dx.doi.org/10.1002/jnm.2822]
[http://dx.doi.org/10.1109/JPROC.2010.2070470]
[http://dx.doi.org/10.1109/LED.2008.2005650]
[http://dx.doi.org/10.1007/s10470-020-01765-z]
[http://dx.doi.org/10.1142/S0218126621501176]
[http://dx.doi.org/10.1088/0957-4484/4/1/004 ] [PMID: 21727566]
[http://dx.doi.org/10.1002/cta.2886]
[http://dx.doi.org/10.1007/s11227-019-02962-y]
[http://dx.doi.org/10.1007/s10773-020-04499-w]
[http://dx.doi.org/10.1016/j.compeleceng.2020.106658]
[http://dx.doi.org/10.1002/cta.2807]
[http://dx.doi.org/10.1016/j.nancom.2020.100298]
[http://dx.doi.org/10.1109/TVLSI.2020.3013724]
[http://dx.doi.org/10.1007/s10773-019-04262-w]
[http://dx.doi.org/10.1080/03772063.2020.1831411]
[http://dx.doi.org/10.1109/TNANO.2020.2969166]
[http://dx.doi.org/10.1016/j.micpro.2019.102944]
[http://dx.doi.org/10.1007/s40089-020-00300-2]
[http://dx.doi.org/10.1007/s10773-019-04210-8]
[http://dx.doi.org/10.1147/rd.53.0183]
[http://dx.doi.org/10.1109/IWCE.2004.1407356]
[http://dx.doi.org/10.1109/TCAD.2007.907020]
[http://dx.doi.org/10.1016/j.ijleo.2019.03.029]
[http://dx.doi.org/10.1108/CW-10-2019-0138]
[http://dx.doi.org/10.1049/el.2009.2819]
[http://dx.doi.org/10.1186/1556-276X-7-221 ] [PMID: 22507371]
[http://dx.doi.org/10.1016/j.jocs.2015.09.010]
[http://dx.doi.org/10.1016/j.mejo.2012.10.007]
[http://dx.doi.org/10.4236/cs.2013.42020]
[http://dx.doi.org/10.1007/s10773-019-04343-w]
[http://dx.doi.org/10.1166/jctn.2013.2773]
[http://dx.doi.org/10.1016/j.mee.2019.111197]
[http://dx.doi.org/10.1109/TCSII.2020.2989496]
[http://dx.doi.org/10.1007/s10825-016-0804-7]
[http://dx.doi.org/10.1007/s40089-019-00292-8]
[http://dx.doi.org/10.1109/ICBIM.2014.6970972]
[http://dx.doi.org/10.1142/S021812661950141X]
[http://dx.doi.org/10.1142/S021812661850216X]
[http://dx.doi.org/10.1016/j.jnlest.2020.100078]
[http://dx.doi.org/10.1016/j.mejo.2015.03.016]
[http://dx.doi.org/10.1007/s42341-019-00166-y]
[http://dx.doi.org/10.1016/j.compeleceng.2020.106712]
[http://dx.doi.org/10.1007/s11082-021-03294-z]
[http://dx.doi.org/10.1142/S0218126618501153]
[http://dx.doi.org/10.1007/s10825-017-0986-7]
[http://dx.doi.org/10.1007/s11082-021-03127-z]
[http://dx.doi.org/10.1007/s11107-020-00915-7]
[http://dx.doi.org/10.1016/j.micpro.2016.09.015]
[http://dx.doi.org/10.1016/j.aej.2017.01.022]
[http://dx.doi.org/10.1007/s10773-019-04069-9]
[http://dx.doi.org/10.1016/j.rinp.2017.04.005]
[http://dx.doi.org/10.1155/2019/1675169]
[http://dx.doi.org/10.1016/j.physb.2018.09.029]
[http://dx.doi.org/10.1109/TNANO.2003.820815]
[http://dx.doi.org/10.1109/TNANO.2005.851278]
[http://dx.doi.org/10.1002/jnm.2907]
[http://dx.doi.org/10.1016/j.mejo.2014.10.003]
[http://dx.doi.org/10.1016/j.ijleo.2021.168463]
[http://dx.doi.org/10.1016/j.ijleo.2015.12.119]
[http://dx.doi.org/10.1049/cds2.12083]
[http://dx.doi.org/10.1007/s11227-020-03478-6]
[http://dx.doi.org/10.1007/s11082-021-03179-1]
[http://dx.doi.org/10.1108/CW-08-2020-0199]
[http://dx.doi.org/10.1016/j.microrel.2013.09.018]
[http://dx.doi.org/10.1080/02564602.2021.1914205]
[http://dx.doi.org/10.1166/jnn.2015.9608 ] [PMID: 26353707]
[http://dx.doi.org/10.1007/s11227-020-03320-z]
[http://dx.doi.org/10.1007/s11227-021-03693-9]
[http://dx.doi.org/10.1002/cta.3125]