Relevant bibliographies by topics / Computational Nano Science

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Computational Nano Science'

Author: Grafiati
Published: 6 September 2023
Last updated: 31 July 2025

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Journal articles on the topic "Computational Nano Science"

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Ghafooriadl, Naser, Sohrab Asadzadeh Olghi, and Ali Moghani. "Computational Algorithms for Topological Cycle Indices of Tert-Butyl Alcohol by Computational Science." Defect and Diffusion Forum 312-315 (April 2011): 39–44. http://dx.doi.org/10.4028/www.scientific.net/ddf.312-315.39.

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Recently, the dominant classes and integer-valued characters of un-matured full non-rigid group of tert-butyl alcohol has been found by the third author (see, J. Nano Res. 11, 7-11, 2010). In this paper, the unit subdued cycle index table introduced by S. Fujita for the above molecule is successfully derived for the first time.
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Kisała, Joanna, Kinga I. Hęclik, Krzysztof Pogocki, and Dariusz Pogocki. "Essentials and Perspectives of Computational Modelling Assistance for CNS-oriented Nanoparticle-based Drug Delivery Systems." Current Medicinal Chemistry 25, no. 42 (2019): 5894–913. http://dx.doi.org/10.2174/0929867325666180517095742.

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The blood-brain barrier (BBB) is a complex system controlling two-way substances traffic between circulatory (cardiovascular) system and central nervous system (CNS). It is almost perfectly crafted to regulate brain homeostasis and to permit selective transport of molecules that are essential for brain function. For potential drug candidates, the CNSoriented neuropharmaceuticals as well as for those of primary targets in the periphery, the extent to which a substance in the circulation gains access to the CNS seems crucial. With the advent of nanopharmacology, the problem of the BBB permeabili
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Grujicic, M., JS Snipes, and S. Ramaswami. "Multi-scale computational analysis of the nano-indentation and nano-scratch testing of Kevlar® 49 single fibers." Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications 232, no. 6 (2016): 495–513. http://dx.doi.org/10.1177/1464420716635851.

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To carry out virtual nano-indentation and nano-scratch Kevlar® 49 single-fiber tests, a multi-scale computational framework has been developed and employed. Such tests are generally conducted to determine fiber local properties, as well as to provide some insight into the interaction of hard nano-particles with the fibers. The Kevlar® fabric-based soft armor is infused with these nano-particles for improved ballistic resistance, and tip geometry of the nano-indentation/-scratch probes is selected to match nano-particle size and geometry. Due to the fact that Kevlar® 49 fibers (typical diameter
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LAMBA, V. K., O. P. GARG, and D. ENGLES. "SCATTERING IN NANO-FILMS." Journal of Multiscale Modelling 04, no. 02 (2012): 1250007. http://dx.doi.org/10.1142/s1756973712500072.

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In this communication, a quantum mechanical technique for treatment of effects of scattering transport at nanoscale in thin films is discussed. We implemented a rigorous treatment of scattering within the NEGF simulation platform. Results obtained by applying the rigorous scattering model to simulate the devices were used as a benchmark to validate a simple computationally-efficient, phenomenological treatment of scattering. The NEGF method is used to study the effect of electron confinement on silicon nano-films and wires. Electron confinement results in almost a factor of 3 decreases in the
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Alavinasab, A., R. Jha, G. Ahmadi, C. Cetinkaya, and I. Sokolov. "Computational modeling of nano-structured glass fibers." Computational Materials Science 44, no. 2 (2008): 622–27. http://dx.doi.org/10.1016/j.commatsci.2008.05.004.

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Chong, Ken P. "Nano Science and Engineering in Solid Mechanics." Acta Mechanica Solida Sinica 21, no. 2 (2008): 95–103. http://dx.doi.org/10.1007/s10338-008-0812-7.

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Hajder, Piotr, and Łukasz Rauch. "Moving Multiscale Modelling to the Edge: Benchmarking and Load Optimization for Cellular Automata on Low Power Microcomputers." Processes 9, no. 12 (2021): 2225. http://dx.doi.org/10.3390/pr9122225.

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Numerical computations are usually associated with the High Performance Computing. Nevertheless, both industry and science tend to involve devices with lower power in computations. This is especially true when the data collecting devices are able to partially process them at place, thus increasing the system reliability. This paradigm is known as Edge Computing. In this paper, we propose the use of devices at the edge, with lower computing power, for multi-scale modelling calculations. A system was created, consisting of a high-power device—a two-processor workstation, 8 RaspberryPi 4B microco
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Dubey, A., G. Sharma, C. Mavroidis, M. S. Tomassone, K. Nikitczuk, and M. L. Yarmush. "Computational Studies of Viral Protein Nano-Actuators." Journal of Computational and Theoretical Nanoscience 1, no. 1 (2004): 18–28. http://dx.doi.org/10.1166/jctn.2003.003.

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Sankaran, Krishnaswamy. "Recent Trends in Computational Electromagnetics for Defence Applications." Defence Science Journal 69, no. 1 (2019): 65–73. http://dx.doi.org/10.14429/dsj.69.13275.

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Innovations in material science, (nano) fabrication techniques, and availability of fast computers are rapidly changing the way we design and develop modern defence applications. When we want to reduce R&D and the related trial-and-error costs, virtual modelling and prototyping tools are valuable assets for design engineers. Some of the recent trends in computational electromagnetics are presented highlight the challenges and opportunities . Why researchers should equip themselves with the state-of-the-art tools with multiphysics and multiscale capabilities to design and develop modern def
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Khitun, Alexander, and Kang L. Wang. "Nano scale computational architectures with Spin Wave Bus." Superlattices and Microstructures 38, no. 3 (2005): 184–200. http://dx.doi.org/10.1016/j.spmi.2005.07.001.

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Dissertations / Theses on the topic "Computational Nano Science"

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Dahl, Anna Caroline E. "Membrane protein mechanotransduction : computational studies and analytics development." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:67798647-8ed5-46e0-bde9-c71235fe70ba.

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Membrane protein mechanotransduction is the altered function of an integral membrane protein in response to mechanical force. Such mechanosensors are found in all kingdoms of life, and increasing numbers of membrane proteins have been found to exhibit mechanosensitivity. How they mechanotransduce is an active research area and the topic of this thesis. The methodology employed is classical molecular dynamics (MD) simulations. MD systems are complex, and two programs were developed to reduce this apparent complexity in terms of both visual abstraction and statistical analysis. Bendix detects an
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Kabiraj, Arnab. "High-Throughput Computational Techniques for Discovery of Application-Specific Two-Dimensional Materials." Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5852.

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Two-dimensional (2D) materials have revolutionized the field of materials science since the successful exfoliation of graphene in 2004. Consequently, the advances in computational science have resulted in massive generic databases for 2D materials, where the structure and the basic properties are predicted using density functional theory (DFT). However, discovering material for a given application from these vast databases is a challenging feat. In this thesis, we have developed various automated high-throughput computational pipelines combining DFT and machine learning (ML) to assess the sui
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Bhattacharya, Amrita. "FIRST-PRINCIPLES STUDY OF FUNCTIONALIZED GRAPHENE AND ITS DERIVATIVES." Thesis, 2019. http://hdl.handle.net/10821/8322.

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In this thesis work, it has been studied the electronic properties of graphene and graphene like planar nano-sheets. It has been specifically tried to address the problem of band gap engineering in the native as well as functionalized derivatives of graphene and graphene-like planar nanomaterials. In chapter-3, we have solved the tight binding Hamiltonian of graphene. It shows that in a pristine graphene sheet, there is Dirac Cone like merging between the valence band and the conduction band. As a result of which the electrons are highly mobile and shows finite conductivity even at 0 K. Theref
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Books on the topic "Computational Nano Science"

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A, Golovin A., Nepomni͡ashchiĭ A. A, and NATO Public Diplomacy Division, eds. Self-assembly, pattern formation and growth phenomena in nano-systems. Springer, 2006.

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From Nano to Space: Applied Mathematics Inspired by Roland Bulirsch. Springer, 2007.

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Nepomnyashchy, Alexander A., and Alexander A. Golovin. Self-Assembly, Pattern Formation and Growth Phenomena in Nano-Systems: Proceedings of the NATO Advanced Study Institute, held in St. Etienne de Tinee, ... 11, 2004. Springer, 2014.

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Succi, Sauro. The Lattice Boltzmann Equation. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199592357.001.0001.

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Over the past near three decades, the Lattice Boltzmann method has gained a prominent role as an efficient computational method for the numerical simulation of a wide variety of complex states of flowing matter across a broad range of scales, from fully developed turbulence, to multiphase micro-flows, all the way down to nano-biofluidics and lately, even quantum-relativistic subnuclear fluids. After providing a self-contained introduction to the kinetic theory of fluids and a thorough account of its transcription to the lattice framework, this book presents a survey of the major developments w
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Hoang, Bao Hung, Cong Phap Huynh, Gottfried Vossen, Bogdan Trawiński, and Ngoc Thanh Nguyen. Computational Collective Intelligence: 12th International Conference, ICCCI 2020, Da Nang, Vietnam, November 30-December 3, 2020, Proceedings. Springer International Publishing AG, 2020.

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Book chapters on the topic "Computational Nano Science"

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Mukherjee, Kasturi, Arpan Deyasi, and Deepam Gangopadhyay. "Quantized conductance characteristics of Nano–MESFET under optical illumination." In Computational Science and Engineering. CRC Press, 2016. http://dx.doi.org/10.1201/9781315375021-54.

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Lee, Kwangyong, Woojin Lee, Juil Kim, and Kiwon Chong. "A Technique for Code Generation of USN Applications Based on Nano-Qplus." In Computational Science – ICCS 2006. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11758549_120.

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Šuvakov, Milovan, and Bosiljka Tadić. "Simulation of the Electron Tunneling Paths in Networks of Nano-particle Films." In Computational Science – ICCS 2007. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72586-2_93.

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Klaedtke, A., J. Hamm, and O. Hess. "5. Simulation of Active and Nonlinear Photonic Nano-Materials in the Finite-Difference Time-Domain (FDTD) Framework." In Computational Materials Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39915-5_5.

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Dubey, Atul, and M. Silvina Tomassone. "Viral Protein Nano-Actuators, Computational Studies of Bio-nanomachines." In Encyclopedia of Complexity and Systems Science. Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-30440-3_577.

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Frijns, A. J. H., S. V. Nedea, A. J. Markvoort, A. A. van Steenhoven, and P. A. J. Hilbers. "Molecular Dynamics and Monte Carlo Simulations for Heat Transfer in Micro and Nano-channels." In Computational Science - ICCS 2004. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25944-2_85.

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Yanovsky, Yu G. "Nano-Modeling Structure and Micromechanical Properties of Mesoscopic Composite Systems." In Computational Methods in Engineering & Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-48260-4_12.

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Solov’yov, Ilia A., Andrey V. Korol, and Andrey V. Solov’yov. "Introduction to Computational Meso-Bio-Nano (MBN) Science and MBN Explorer." In Multiscale Modeling of Complex Molecular Structure and Dynamics with MBN Explorer. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56087-8_1.

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Huang, D., and J. S. Zhuo. "Molecular Dynamics Simulation of Length Size Effect on Mechanical Properties of Nano-Metal." In Computational Methods in Engineering & Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-48260-4_113.

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Ambrosi, Davide, Pasquale Ciarletta, Elena Danesi, Carlo de Falco, Matteo Taffetani, and Paolo Zunino. "A Multiscale Modeling Approach to Transport of Nano-Constructs in Biological Tissues." In Lecture Notes in Computational Science and Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-73371-5_6.

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Conference papers on the topic "Computational Nano Science"

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Jabbar, Ahmed N., Abdulkareem A. Kadhim, and Samir J. Al-Muraab. "Novel Symbol over Multiplexing Technique for Transmitted Power, Bandwidth and Computational Load Reduction." In 2023 International Conference on Engineering Applied and Nano Sciences (ICEANS). IEEE, 2023. http://dx.doi.org/10.1109/iceans58413.2023.10630490.

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Gonzales, Bryan, Reylina Garcia Tayactac, Ricky Umali, Jaime Honra, and Aldrin Calderon. "CFD Simulation of a Circulating Fluidized Bed Boiler to Improve Air Distribution for Satisfactory Fluidization." In 2024 8th International Conference on Materials Engineering and Nano Sciences & 2024 8th International Conference on Material Engineering and Manufacturing. Trans Tech Publications Ltd, 2024. http://dx.doi.org/10.4028/p-lu6fwm.

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This study focuses on the design of circulating fluidized bed (CFB) boilers, emphasizing optimizing the distribution of primary and secondary air to achieve better fluidization behavior, leading to better combustion performance. ANSYS Fluent is used to conduct Computational Fluid Dynamics (CFD) simulation using the Eulerian multiphase model and the standard k-epsilon turbulence model to model and analyze the fluidization in CFB. Performance evaluation metrics assess fluidization quality based on coal volume fraction, air and coal velocity, and pressure. The total air mass flow rate was set to
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Junpeng, Yuan, Zhu Donghua, Huang Jin, Bao Hailong, and Yang Chunning. "A Text Mining Framework to Support Nano Science and Technology Management." In Multiconference on "Computational Engineering in Systems Applications. IEEE, 2006. http://dx.doi.org/10.1109/cesa.2006.4281982.

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Etminan, Maryam, George Maroulis, and Theodore E. Simos. "The Decomposition of Doubly Charged Silver Nano Clusters." In COMPUTATIONAL METHODS IN SCIENCE AND ENGINEERING: Advances in Computational Science: Lectures presented at the International Conference on Computational Methods in Sciences and Engineering 2008 (ICCMSE 2008). AIP, 2009. http://dx.doi.org/10.1063/1.3225438.

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Norlina, M. S., P. Mazidah, N. D. Md Sin, and M. Rusop. "Computational intelligence technique in optimization of nano-process deposition parameters." In 2015 7th Computer Science and Electronic Engineering (CEEC). IEEE, 2015. http://dx.doi.org/10.1109/ceec.2015.7332722.

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Sayed, Ahmed, and Hisham El-Shishiny. "Computational Experience with Nano-material Science Quantum Monte Carlo Modeling on BlueGene/L." In 2009 Fifth International Conference on MEMS NANO, and Smart Systems. IEEE, 2009. http://dx.doi.org/10.1109/icmens.2009.32.

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Maroulis, George, Demetrios Xenides, Panaghiotis Karamanis, George Maroulis, and Theodore E. Simos. "Computational Quantum Chemistry: From Atoms and Molecules to Clusters and Nano-objects." In COMPUTATIONAL METHODS IN SCIENCE AND ENGINEERING: Advances in Computational Science: Lectures presented at the International Conference on Computational Methods in Sciences and Engineering 2008 (ICCMSE 2008). AIP, 2009. http://dx.doi.org/10.1063/1.3225298.

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Yuan, Junpeng, Huang Jin, Donghua Zhu, Hailong Bao, and Chunning Yang. "A Text Mining Framework to Support Nano Science and Technology Management." In The Proceedings of the Multiconference on "Computational Engineering in Systems Applications". IEEE, 2006. http://dx.doi.org/10.1109/cesa.2006.313470.

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Machowski, Lukasz, and Tshilidzi Marwala. "Nano Version Control and "Robots of Robots" – Data Driven, Regenerative Production Code." In 2021 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2021. http://dx.doi.org/10.1109/csci54926.2021.00360.

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Fey, Florian, Alexander Gerwing, and Sergei Gorlatch. "Towards a Generic Framework for GPU-Parallelized Simulations of Light-Driven Nano-Particles." In 2022 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2022. http://dx.doi.org/10.1109/csci58124.2022.00245.

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You might also be interested in the extended bibliographies on the topic 'Computational Nano Science' for particular source types:
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