Computational nanotechnology

Computational nanotechnology is a branch of nanotechnology concerned with the development and use of computer-based models for understanding, analysing and predicting the behaviour or properties of systems relevant to nanotechnology.

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News & Views | 26 July 2022

Resistive memories stack up
- Injune Yeo
- & Jae-sun Seo
Nature Electronics 5, 414-415

Latest Research and Reviews

Research
22 April 2022 | Open Access

Simulating a chemically fueled molecular motor with nonequilibrium molecular dynamics

Molecular motors move in response to an imbalance between concentrations of fuel and waste molecules. Here, the authors simulate such non-equilibrium conditions to characterize a model motor’s performance and mechanism of operation.
- Alex Albaugh
- & Todd R. Gingrich
Nature Communications 13, 2204
Research
21 February 2022 | Open Access

MHD mixed convection and entropy generation of CNT-water nanofluid in a wavy lid-driven porous enclosure at different boundary conditions
- Hameed K. Hamzah
- , Farooq H. Ali
- & M. Hatami
Scientific Reports 12, 2881
Research
10 January 2022 | Open Access

Direct matching between the flow factor approach model and molecular dynamics simulation for nanochannel flows
- Chuntao Jiang
- & Yongbin Zhang
Scientific Reports 12, 396
Reviews | 29 November 2021

Quantum-coherent nanoscience

Although quantum physics underpins the behaviour of nanoscale objects, its role in nanoscience has been mostly limited to determining the static, equilibrium properties of small systems. This Review describes seminal developments and new directions for the explicit exploitation of quantum coherence in nanoscale systems, a research area termed quantum-coherent nanoscience.
- Andreas J. Heinrich
- , William D. Oliver
- & Andrea Morello
Nature Nanotechnology 16, 1318-1329
Research
18 November 2021 | Open Access

The MHD Newtonian hybrid nanofluid flow and mass transfer analysis due to super-linear stretching sheet embedded in porous medium
- U. S. Mahabaleshwar
- , T. Anusha
- & M. Hatami
Scientific Reports 11, 22518
Research
02 November 2021 | Open Access

Improving the self-assembly of bioresponsive nanocarriers by engineering doped nanocarbons: a computational atomistic insight
- Mohammad Khedri
- , Nima Beheshtizadeh
- & Sima Rezvantalab
Scientific Reports 11, 21538

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News and Comment

News & Views | 26 July 2022

Resistive memories stack up

Three-dimensional computing systems made of vertically integrated complementary metal–oxide–semiconductor circuits and layered resistive memory can perform analogue computing-in-memory with high energy efficiency.
- Injune Yeo
- & Jae-sun Seo
Nature Electronics 5, 414-415
Research Highlights | 06 January 2015

Simulating water slippage
- Fabio Pulizzi
Nature Nanotechnology, 1
Research Highlights | 06 January 2015

Our choice from the recent literature

Nature Nanotechnology 10, 17
Research Highlights | 05 March 2013

Nanoparticles go with the flow
- Alberto Moscatelli
Nature Nanotechnology, 1
Correspondence | 05 February 2013

Standardizing data
- Nathan A. Baker
- , Juli D. Klemm
- & Susanna-Assunta Sansone
Nature Nanotechnology 8, 73-74
Research Highlights | 06 December 2011

More is better

Nature Nanotechnology, 1

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Computational nanotechnology

Featured

Resistive memories stack up

Latest Research and Reviews

Simulating a chemically fueled molecular motor with nonequilibrium molecular dynamics

MHD mixed convection and entropy generation of CNT-water nanofluid in a wavy lid-driven porous enclosure at different boundary conditions

Direct matching between the flow factor approach model and molecular dynamics simulation for nanochannel flows

Quantum-coherent nanoscience

The MHD Newtonian hybrid nanofluid flow and mass transfer analysis due to super-linear stretching sheet embedded in porous medium

Improving the self-assembly of bioresponsive nanocarriers by engineering doped nanocarbons: a computational atomistic insight

News and Comment

Resistive memories stack up

Simulating water slippage

Our choice from the recent literature

Nanoparticles go with the flow

Standardizing data

More is better

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