Multidisciplinary approaches in theory, applications and modeling of nanoscale systems

Roderick V.N. Melnik

Nanoscale Systems: Mathematical Modeling, Theory and Applications (2013)

  • Volume: 2, page 1-9
  • ISSN: 2299-3290

Abstract

top
This editorial provides an overview of both fundamental and applied research areas covered by the journal of Nanoscale Systems: Mathematical Modeling, Theory and Applications (NanoMMTA), as well as of articles published in the journal inaugural volume. The unique feature of NanoMMTA is its focus on the interface between the study, development, and application of systems at the nanoscale with theoretical methods and experimental techniques on the one hand and mathematical, statistical, and computational tools on the other. NanoMMTA is the first international, interdisciplinary, peer-reviewed journal focusing specifically on this interface. This emerging multidisciplinary field at the interface of mathematical modeling, nanoscience and nanotechnology includes applications and advancements of these tools in all of the disciplines facing the challenges associated with the nanoscale systems.

How to cite

top

Roderick V.N. Melnik. "Multidisciplinary approaches in theory, applications and modeling of nanoscale systems." Nanoscale Systems: Mathematical Modeling, Theory and Applications 2 (2013): 1-9. <http://eudml.org/doc/266560>.

@article{RoderickV2013,
abstract = {This editorial provides an overview of both fundamental and applied research areas covered by the journal of Nanoscale Systems: Mathematical Modeling, Theory and Applications (NanoMMTA), as well as of articles published in the journal inaugural volume. The unique feature of NanoMMTA is its focus on the interface between the study, development, and application of systems at the nanoscale with theoretical methods and experimental techniques on the one hand and mathematical, statistical, and computational tools on the other. NanoMMTA is the first international, interdisciplinary, peer-reviewed journal focusing specifically on this interface. This emerging multidisciplinary field at the interface of mathematical modeling, nanoscience and nanotechnology includes applications and advancements of these tools in all of the disciplines facing the challenges associated with the nanoscale systems.},
author = {Roderick V.N. Melnik},
journal = {Nanoscale Systems: Mathematical Modeling, Theory and Applications},
keywords = {Systems at the nanoscale; Physics and chemistry; Biology and life sciences; Materials science; Medicine and engineering; Mathematical, statistical and computational sciences; Cross-disciplinary research collaboration},
language = {eng},
pages = {1-9},
title = {Multidisciplinary approaches in theory, applications and modeling of nanoscale systems},
url = {http://eudml.org/doc/266560},
volume = {2},
year = {2013},
}

TY - JOUR
AU - Roderick V.N. Melnik
TI - Multidisciplinary approaches in theory, applications and modeling of nanoscale systems
JO - Nanoscale Systems: Mathematical Modeling, Theory and Applications
PY - 2013
VL - 2
SP - 1
EP - 9
AB - This editorial provides an overview of both fundamental and applied research areas covered by the journal of Nanoscale Systems: Mathematical Modeling, Theory and Applications (NanoMMTA), as well as of articles published in the journal inaugural volume. The unique feature of NanoMMTA is its focus on the interface between the study, development, and application of systems at the nanoscale with theoretical methods and experimental techniques on the one hand and mathematical, statistical, and computational tools on the other. NanoMMTA is the first international, interdisciplinary, peer-reviewed journal focusing specifically on this interface. This emerging multidisciplinary field at the interface of mathematical modeling, nanoscience and nanotechnology includes applications and advancements of these tools in all of the disciplines facing the challenges associated with the nanoscale systems.
LA - eng
KW - Systems at the nanoscale; Physics and chemistry; Biology and life sciences; Materials science; Medicine and engineering; Mathematical, statistical and computational sciences; Cross-disciplinary research collaboration
UR - http://eudml.org/doc/266560
ER -

References

top
  1. A. V. Antoniouk and R.V.N. Melnik. Scientific frontiers at the interface of mathematics and life sciences. Mathematics and Life Sciences, De Gruyter, Berlin, New York, pp.1–16 (2012). 
  2. R.V.N. Melnik and I. S. Kotsireas, Interconnected challenges and new perspectives in applied mathematical and computational sciences. Advances in Applied Mathematics, Modeling, and Computational Science, Fields Institute Communications 66, Springer, New York, pp. 1–10 (2013). 
  3. K. Tai, M. Dao, S. Suresh, A. Palazoglu, and C. Ortiz. Nanoscale Heterogeneity Promotes Energy Dissipation in Bone. Nature Materials, 6, 454–462, (2007). 
  4. L. Adler-Abramovich, D. Aronov, P. Beker, M. Yevnin, S. Stempler, L. Buzhansky, et al. Self-assembled arrays of peptide nanotubes by vapour deposition. Nature Nanotechnology, 4 (12), 849–854 (2009). 
  5. H. Q. Shi, A.S. Barnard, and I.K. Snook. Quantum mechanical properties of graphene nano-flakes and quantum dots. Nanoscale, 4 (21), 6761–6767 (2012), DOI: 10.1039/c2nr31354e. 
  6. J. Zivkovic and B. Tadic. Nanonetworks: The Graph Theory Framework for Modeling Nanoscale Systems. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 2, 30 (2013), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2013-0003. Zbl1272.05211
  7. N. O. Weiss, H.L. Zhou, L. Liao, Y. Liu, S. Jiang, Y. Huang, et al. Graphene: An Emerging Electronic Material. Advanced Materials, 24 (43), 5782–5825 (2012), DOI: 10.1002/adma.201201482. 
  8. L. Cademartiri, K. J. M. Bishop, P.W. Snyder, and G.A. Ozin. Using shape for self-assembly. Philosophical Transactions of the Royal Society A - Mathematical Physical and Engineering Sciences, 370 (1969), Special Issue: SI, 2824–2847 (2012), DOI: 10.1098/rsta.2011.0254. 
  9. R.V.N. Melnik and A. Povitsky, editors. Modelling coupled and transport phenomena in nanotechnology. Journal of Computational and Theoretical Nanoscience, 3 (4) (2006). 
  10. S. Prabhakar, R. V. N. Melnik, P. Neittaanmaki, and T. Tiihonen, Coupled electromechanical effects in wurtzite quantum dots with wetting layers in gate controlled electric fields: The multiband case. Physica E: Low-dimensional Systems and Nanostructures 46, 97–104 (2012). 
  11. S. Prabhakar, R.V.N. Melnik, P. Neittaanmaki, and T. Tiihonen, Coupled magneto-thermo-electromechanical effects and electronic properties of quantum dots. Journal of Computational and Theoretical Nanoscience 10, 550–563 (2013). 
  12. P. Tiwary and A. van de Walle. Hybrid deterministic and stochastic approach for efficient atomistic simulations at long time scales. Physical Review B, 84 (10), 100301 (2011) DOI: 10.1103/PhysRevB.84.100301. 
  13. M. Paliy, R. Melnik, and B. A. Shapiro. Coarse-graining RNA nanostructures for molecular dynamics simulations. Physical Biology, 7 (3), 036001 (2010). 
  14. A. Cambi and D.S. Lidke. Nanoscale Membrane Organization: Where Biochemistry Meets Advanced Microscopy. ACS Chemical Biology, 7 (1), 139–149 (2012), DOI: 10.1021/cb200326g. 
  15. D. R. Han, S. Pal, Y. Liu, H. Yan. Folding and cutting DNA into reconfigurable topological nanostructures. Nature Nanotechnology, 5 (10), 712–717 (2010), DOI: 10.1038/nnano.2010.193. 
  16. D.N. Kim, F. Kilchherr, H. Dietz, and M. Bathe. Quantitative prediction of 3D solution shape and flexibility of nucleic acid nanostructures. Nucleic Acids Research, 40 (7), 2862–2868 (2012), DOI: 10.1093/nar/gkr1173. 
  17. M. Gu, K. Wiesner, E. Rieper, and V. Vedral. Quantum mechanics can reduce the complexity of classical models. Nature Communications, 3, 762 (2012), DOI: 10.1038/ncomms1761. 
  18. Y. F. Dufrene and M.F. Garcia-Parajo. Recent progress in cell surface nanoscopy: Light and force in the near-field. Nano Today, 7 (5), 390–403 (2012), DOI: 10.1016/j.nantod.2012.08.002. 
  19. F.M. Borodich, B.A. Galanov, S.N. Gorb, M.Y. Prostov, Y.I. Prostov, and Suarez-Alvarez, M.M. An inverse problem for adhesive contact and non-direct evaluation of material properties for nanomechanics applications. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 80–92 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0006. 
  20. P. R. Srinivas, M. Philbert, T.Q. Vu, Q. R. Huang, J.L. Kokini, E. Saos, et al. Nanotechnology Research: Applications in Nutritional Sciences. Journal of Nutrition, 140 (1), 119-124 (2010), DOI: 10.3945/jn.109.115048. 
  21. C. Y. Fong, M. Shaughnessy, L. Damewood, and L. H. Yang. Theory, Experiment and Computation of Half Metals for Spintronics: Recent Progress in Si-based Materials. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 1–22 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0001. 
  22. H.A. Thorolfsson, A. Manolescu, D.C. Marinescu, and V. Gudmundsson. Coulomb interaction effects on the spin polarization and currents in quantum wires with spin orbit interaction. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 23–37 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0002. Zbl1273.82084
  23. A. Sellitto and F.X. Alvarez. Non-Fourier heat removal from hot nanosystems through graphene layer. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 38–47 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0003. Zbl1273.80004
  24. A. Sowa. Signals generated in memristive circuits. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 48–57 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0004. Zbl1273.42037
  25. J.-L. Liu. Mathematical modeling of semiconductor quantum dots based on the nonparabolic effective-mass approximation. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 58–79 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0005. Zbl1273.65162
  26. A. Borzi. Quantum optimal control using the adjoint method. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 93–111 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0007. Zbl1273.35230
  27. F.X. Alvarez, V.A. Cimmelli, D. Jou, A. Sellitto. Mesoscopic description of boundary effects in nanoscale heat transport. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 112–142 (2012), ISSN (Online) 2299- 3290, DOI: 10.2478/nsmmt-2012-0008. Zbl1273.74003
  28. W. Hoiles, V. Krishnamurthy, B. Cornell. Mathematical Models for Sensing Devices Constructed out of Artificial Cell Membranes. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 143–171 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0009. 
  29. N. Ebrahimi, M. Shehadeh, K. McCullough. Bayesian Analysis for Robust Synthesis of Nanostructures. Nanoscale Systems: Mathematical Modeling, Theory and Applications, 1, 172–186 (2012), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2012-0010. 
  30. S. K. Singh and F. M. Peeters. Vibrational Properties of Nanographene Nanoscale Systems: Mathematical Modeling, Theory and Applications, 2, 10–29 (2013), ISSN (Online) 2299-3290, DOI: 10.2478/nsmmt-2013-0002. 

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

                
Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.