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Electronic characterization of bio-molecular nanoscale devices is important in the new edge of nanotechnology and the field of nanoelectronics. In this new era, the molecular transmission properties of the Adenine bio-molecular optical switch are predicted using Density Functional Theory along with Non-Equilibrium Green's Function-based First Principle approach and this phenomenon is supported with Machine Learning based algorithms. The photo-induced switching characteristics are observed for the bi-directional bio-molecular switch for both forward and reverse bias conditions. This switching behaviour converts the position of the bio-molecular switch to its straightened and 60° twisted form. The electrical doping process plays an important role in generating p and n regions at the two ends of the switch. In this experiment, gold electrodes are used as the supporting anchor of the Adenine molecules. The HOMO–LUMO gap and I–V characteristics of the bio-molecular switch are analyzed using first principle formalisms and compared with the Machine learning approach. This ML approach helps design the future-generation prediction model for the nano-scale electronic device simulation process. This prediction model can be obtained without knowing the switching characteristics and also without knowing all-time sequence generating waveforms but only observing the waveform prediction for up to a certain period sequence.

Biomolecular modeling and its associated analytical software simulation tools have a significant role in the rapid progress of bio-inspired semiconductor technologies. This paper presents the implementation of logic gates using molecular modeling of a cytosine-based single-walled nanotube. Density functional theory in and the nonequilibrium Green’s function-based first-principles approach are used to perform the quantum mechanical calculations for the electronic transmission within the nanotube. The gated cytosine single-walled nanotube shows high current-voltage response during room-temperature operation where the electrode voltage is kept at ± 0.02 V. This is a first attempt towards the circuit-level modeling of logic gates using a cytosine nanotube. The quantum transport phenomenon of this analytical model is investigated using an atomistic software simulation technique. The basic logic gates and XNOR gate are implemented with the study of the current-voltage characteristics. The maximum current observed during the simulation process is 52.6 μA. Moreover, the local device density at different energy levels proves the candidature of cytosine nanotubes as logic gates. The transmission spectrum analysis also confirms the high channel conductivity at the central scattering region of the nanotube.

One of the emerging areas of today’s research arena is molecular modeling and molecular computing. The molecular logic gate can be theoretically implemented from single-strand DNA which consists of four basic nucleobases. In this study, the electronic transmission characteristics of DNA chain are investigated to form the logic gate. This biomolecular single-strand DNA chain is passed through an electrically doped gallium-arsenide nano-pore to achieve reasonably improved transmission along <1 1 1> direction. Current-voltage characteristic and device density of states with HOMO-LUMO plot of the device are explained along with the conductivity of the device to confirm the characteristics of some important logic gates like a universal gate. Ultimately the property of resistivity proves the law of Boolean logic of AND gate and universal logic gate, viz., NAND and NOR gate. All the electronic properties of the Boolean logic gate are explored based on the first principle approach by non-equilibrium Green’s function coupled with density functional theory in room temperature.

This study aims to analyze the validity and reliability of the algebraic reasoning question instrument. The total number of questions in this study were 8 questions which were done by 107 junior high school students in Indonesia. Based on the results of the analysis using the Rasch model, it was found that the instrument had Cronbach’s alpha (KR-20) in the medium category, the item reliability was excellent, and the person reliability was in the low category. This shows that the instrument is a very reliable instrument for assessing students’ algebraic reasoning but students were unable to solve them well. Meanwhile, the results of the validity found that Q8 was not the fit criteria for MNSQ Outfit, ZSTD Outfit, and PTMEA-CORR. As for person fit, only six students showed a misfit, which indicated that other students gave a meaningful response to Rasch’s analysis.

Context The Adenine-based nanotube is theoretically designed, and its transmission spectra are investigated. The quantum-confined Adenine nanotube shows electronic transmission of the carrier at minimum stress. In this paper, the prediction of transmission spectra of the quantum-confined bio-molecular nanotube is investigated and deeply studied. Molecular level structure prediction and their electronic characterization can be possible with ab initio accuracy using a machine learning algorithmic approach. At the molecular level, it is difficult to predict quantum transmission spectra as these results are always hampered by the carrier backscattering effect. However, mostly these predictive models are available for intrinsic semi-conducting materials and other inorganic structures. Methods Machine learning algorithms are designed to predict the electronic properties of the nano-scale structure. This task is even more difficult when quantum-confined molecular arrangements are considered, whose transmission spectra are sensitive to the confinements applied. This paper presents an effective machine learning algorithms framework for predicting transmission spectra of quantum-confined nanotubes from their geometries. In this paper, we consider regression machine learning algorithms to find maximum accuracy with varying configurations and geometries to excerpt their atoms’ local environment information. The Hamiltonian components are then used to enable the utilization of the information to predict the electronic structure at any arbitrary sampling point or k-point. The theoretical basics introduced in this process help to capture and incorporate minor changes in quantum confinements into transmission spectra and provide the framework algorithm with more accuracy. This paper shows the ability to predict the accurate algorithmic models of the Adenine nanotube. In this framework, we have considered a tiny data set to achieve a rapid and reliable method for electronic structure determination and also propose the best algorithm for predictive model analysis.

Computational study plays an important role to discover the potential ofthe bio-inspired nano scale molecular devices. Density Functional Theory (DFT) is one of the popular methods to calculate the properties of the molecules which can not be possible with ab initio process, preferably for transition metals. This method is important for electronic structure calculation along with structure of molecules, atoms and solids can also be calculated using this DFT method. It is the quantitative method to understand the material properties using the laws of fundamental quantum mechanics. The key benefit of Non Equilibrium Greens' Function (NEGF) is that it preserves the wave character of the electrons, which leads to a extremely precise description of nanoscale. Combining theses DFT and NEGF calculation first principle approach reveal the quantum-ballistic properties of atomic scale electronic structures which is therefore attracts the researchers for their innovative calculations for nano scale device modelling. In this paper, we briefly discuss the review on various bio-molecular devices and their significances. Now-a-days bio inspired devices show more attractions due to their versatility compared to the conventional electronic devices. These nano scale devices are popular due to their performance, speed and high charge transmission properties compared to other conventional semi-conductor devices. This review work presents some experimental works at the molecular level along with a variety of research works that are performed based on first principle approach. Several case studies prevails the importance of DFT and NEGF based first principle approach for nano scale device modelling.

Split and merge segmentation is a popular region-based segmentation scheme for its robustness and computational efficiency. But it is hard to realize for larger size images or video frames in real time due to its iterative sequential data flow pattern. A quad-tree data structure is quite popular for software implementation of the algorithm, where a local parallelism is difficult to establish due to inherent data dependency between processes. In this paper, we have proposed a parallel algorithm of splitting and merging which depends only on local operations. The algorithm is mapped onto a hierarchical cell network, which is a parallel version of Locally Excitory Globally Inhibitory Oscillatory Network (LEGION). Simulation results show that the proposed design is faster than any of the standard split and merge algorithmic implementations, without compromising segmentation quality. The timing performance enhancement is manifested in its Finite State Machine based VLSI implementation in VIRTEX series FPGA platforms. We have also shown that, though segmentation qualitywise split-and-merge algorithm is little bit behind the state-of-the-art algorithms, computational speedwise it over performs those sophisticated and complex algorithms. Good segmentation performance with minimal computational cost enables the proposed design to tackle real time segmentation problem in live video streams. In this paper, we have demonstrated live PAL video segmentation using VIRTEX 5 series FPGA. Moreover, we have extended our design to HD resolution for which the time taken is less than 5 ms rendering a processing throughput of 200 frames per second.

In this study, electrically doped bio-molecular p-i-n field-effect transistor (FET) is designed and its electronic properties are investigated. Density functional theory along with non-equilibrium Green's function based first principle approach is used to design the bio-molecular FET at sub-atomic region. Three Adenine and two Thymine molecules are attached together to form 6.24 nm long and 1.40 nm wide bio p-i-n FET. This device is attached with two platinum electrodes and wrapped with a metallic cylindrical gate at high vacuum. Intrinsic n and p regions can be made possible within a bio-molecular device at room temperature by electrical doping without explicit dopants, which leads to conduct current by the device both in forward and reverse bias. The various quantum mechanical properties have been calculated using Poisson's equations and self-consistent function for the bio-molecular FET. Among these various quantum mechanical properties, the authors obtain high quantum transmission along with satisfactory current for the proposed device during the room temperature operation. The goal of this study is to highlight the design of a bio-molecular p-i-n FET with satisfactory large current using ultra low power dissipation.

Molecular Quantum-dot Cellular Automata is the most promising and challenging technology nowadays for its high operating frequency, extremely high device density and non-cryogenic working temperature. In this paper, we report a First Principle approach based on analytical model of 3-dot Bio Molecular Quantum-dot Cellular Automata. The device is 19.62Å long and this bio molecular Quantum dot Cell has been made with two Adenine Nucleotide bio-molecules along with one Carbazole and one Thiol group. This whole molecular structure is supported onto Gold substrate. In this paper, two Adenine Nucleotides act as two quantum dots and Carbazole acts as another dot. These 3-Quantum-dots are mounted in a tree like structure supported with Thiol group. This model has been demonstrated with Extended Hückel Theory based semi-empirical method. The quantum ballistic transmission and HOMO-LUMO plot support the polarization state change. This state changing ability has been observed for this molecular device. Therefore, this property has been investigated and reported in this paper. HOMO-LUMO plot shows the two logic states along with null state for this 3-dots system. This phenomenon illustrates how the charge transfers take place. Two polarization states along with one additional null state have been obtained for this bio molecular nano device. This molecular device has been operated with 1000THz frequency. This nanoscale design approach will initiate one step towards the modeling of high frequency bio molecular Quantum dot Cell at room temperature.