Related papers: Deep learning framework for carbon nanotubes: mech…
Due to their extraordinary physical and chemical properties carbon nanotubes reveal a promising potential as biomedical agents for heating, temperature sensoring and drug delivery on the cellular level. Filling carbon nanotubes with…
Interfacial friction plays a crucial role in the mechanical properties of carbon nanotube based fibers, composites, and devices. Here we use molecular dynamics simulation to investigate the pressure effect on the friction within carbon…
The structure and elastic properties of (5,5) and (10,10) nanotubes, as well as barriers for relative rotation of the walls and their relative sliding along the axis in a double-walled (5,5)@(10,10) carbon nanotube, are calculated using the…
Solid-state nanofoaming experiments are conducted on two PMMA grades of markedly different molecular weight using CO$_2$ as the blowing agent. The sensitivity of porosity to foaming time and foaming temperature is measured. Also, the…
Carbon nanotubes (CNTs - long tubular carbon nanostructures) belong to the best electron field emitting materials. Based on the experimentally determined electron density in the dual hot filament/DC plasma deposition system the electric…
In the present paper, a temperature-dependent meshless numerical framework based on the thermo-related quasi-continuum constitutive model is developed for predicting the thermal mechanical properties of single-walled carbon nanotubes…
Due to their chiral structure, carbon nanosprings possess unique properties that are promising for nanotechnology applications. The structural transformations of carbon nanosprings in the form of spiral macromolecules derived from planar…
Examination of thermal expansion of two-dimensional (2D) nanomaterials is a challenging theoretical task with either ab-initio or classical molecular dynamics simulations. In this regard, while ab-initio molecular dynamics (AIMD)…
It is difficult to quantify structure-property relationships and to identify structural features of complex materials. The characterization of amorphous materials is especially challenging because their lack of long-range order makes it…
The fundamental quantity governing the mechanical and thermodynamic properties of a crystalline solid is its electronic charge density. Yet, its direct use for the rapid prediction of materials properties remains challenging due to its high…
It is shown by the method of molecular dynamics using a chain model that a multilayer packaging of identical single-walled carbon nanotubes with a diameter of D>2.5 nm located on a flat substrate is a multistable system. The system has many…
Field-scale properties of fractured rocks play crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion…
Single wall carbon nanotubes cooled to cryogenic temperatures are outstanding electronic as well as nano-electromechanical model systems. To probe a largely unperturbed system, we measure a suspended carbon-nanotube device where the…
Conditional computation for Deep Neural Networks (DNNs) reduce overall computational load and improve model accuracy by running a subset of the network. In this work, we present a runtime throttleable neural network (TNN) that can…
Engineering design and scientific analysis rely upon computer simulations of turbulent fluid flows using turbulence models. These turbulence models are empirical and approximate, leading to large uncertainties in their predictions that…
Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond the range of test facilities. This paper proposes a…
The first order phase transition of a water cluster confined in a dynamic single-walled carbon nanotube is investigated using a classical molecular dynamics (MD) method. The formation of ice-nanotube is monitored through the structure…
We review our recent modelling work of carbon nanotubes as potential candidates for heat dissipation in microelectronics cooling. In the first part, we analyze the impact of nanotube defects on their thermal transport properties. In the…
The thermal conductivity, k(T), of bulk single-wall carbon nanotubes (SWNT's) displays a linear temperature dependence at low T that has been attributed to 1D quantization of phonons. To explore this issue further, we have measured the k(T)…
The evaluation of Deep Learning models has traditionally focused on criteria such as accuracy, F1 score, and related measures. The increasing availability of high computational power environments allows the creation of deeper and more…