Deoxyribonucleic acid (DNA) is effective for molecular computation because of its high energy efficiency, high information density, and parallel-computing capability. Although logic implementation using DNA molecules is well established in binary systems (base value of 2) via decoration of hairpin structures on DNA duplexes, systems with base values of >2 (e.g. 3, corresponding to a ternary system) are rarely discussed owing to the complexity of the design and the experimental difficulties with DNA. In this study, DNA rule tiles that participate to form algorithmic DNA crystals exhibiting the ternary representation of an N (N = 1 or 2)-input and 1-output algorithmic assembly are conceived. The number of possible algorithmic patterns is [Formula: see text] in the ternary N-input and 1-output logic gate. Thus, the number of possible rules is 27 (=3) for a 1-input and 1-output algorithmic logic gate and 19 638 (=3) for a 2-input and 1-output algorithmic logic gate. Ternary bit information (i.e. 0-, 1-, and 2-bit) is encoded on rule tiles without hairpins and with short and long hairpins. We construct converged, line-like, alternating, and commutative patterns by implementing specific rules (TR00, TR05, TR07, and TR15, respectively) for the 1-input and 1-output gate and an ascending line-like pattern (with the rule of TR3785) for the 2-input and 1-output gate. Specific patterns generated on ternary-representing rule-embedded algorithmic DNA crystals are visualized via atomic force microscopy, and the errors during the growth of the crystals are analyzed (average error rates obtained for all experimental data are <4%). Our method can easily be extended to a system having base values of >3.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1088/1361-6528/ab5472 | DOI Listing |
Small
August 2022
Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA.
Atomically thin, 2D, and semiconducting transition metal dichalcogenides (TMDs) are seen as potential candidates for complementary metal oxide semiconductor (CMOS) technology in future nodes. While high-performance field effect transistors (FETs), logic gates, and integrated circuits (ICs) made from n-type TMDs such as MoS and WS grown at wafer scale have been demonstrated, realizing CMOS electronics necessitates integration of large area p-type semiconductors. Furthermore, the physical separation of memory and logic is a bottleneck of the existing CMOS technology and must be overcome to reduce the energy burden for computation.
View Article and Find Full Text PDFNanotechnology
November 2019
Department of Physics and Sungkyunkwan Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea.
Deoxyribonucleic acid (DNA) is effective for molecular computation because of its high energy efficiency, high information density, and parallel-computing capability. Although logic implementation using DNA molecules is well established in binary systems (base value of 2) via decoration of hairpin structures on DNA duplexes, systems with base values of >2 (e.g.
View Article and Find Full Text PDFBiosystems
July 2012
Interdisciplinary Computing and Complex Systems Research Group, School of Computer Science, University of Nottingham, Jubilee Campus, UK.
In this paper we detail experimental methods to implement registers, logic gates and logic circuits using populations of photochromic molecules exposed to sequences of light pulses. Photochromic molecules are molecules with two or more stable states that can be switched reversibly between states by illuminating with appropriate wavelengths of radiation. Registers are implemented by using the concentration of molecules in each state in a given sample to represent an integer value.
View Article and Find Full Text PDFNeural Netw
November 1997
Telstra Research Laboratories, Clayton, Australia
We estimate the storage capacity of multilayer perceptron with n inputs, h(1) threshold logic units in the first hidden layer and 1 output. We show that if the network can memorize 50% of all dichotomies of a randomly selected N-tuple of points of R(n) with probability 1, then N=2(nh(1)+1), while at 100% memorization N=nh(1)+1. Furthermore, if the bounds are reached, then the first hidden layer must be fully connected to the input.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!