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molecular dynamics

Nuwan Dewapriya's picture

Characterizing fracture stress of defective graphene samples using shallow and deep artificial neural networks

Abstract: Advanced machine learning methods could be useful to obtain novel insights into some challenging nanomechanical problems. In this work, we employed artificial neural networks to predict the fracture stress of defective graphene samples. First, shallow neural networks were used to predict the fracture stress, which depends on the temperature, vacancy concentration, strain rate, and loading direction.

Jingjie Yeo's picture

Conductive Silk‐Based Composites Using Biobased Carbon Materials

Fresh in Advanced Materials! Synthesis & molecular dynamics modeling of conductive, highly stretchable, flexible, & biocompatible silk‐based composite sensors using biobased carbon materials. https://doi.org/10.1002/adma.201904720

Jingjie Yeo's picture

Postdoctoral position in multiscale computational simulations in the J2 Lab for Engineering Living Materials

http://jingjieyeo.github.io/positions.html I am happy to announce that the website of the J2 Lab for Engineering Living Materials is now live! We're very excited to get cracking in Jan 2020 at the Sibley School of Mechanical and Aerospace Engineering in Cornell University, and we're hiring one postdoc experienced in multiscale computational simulations to kickstart our lab. Please visit our website for more details!

Pär Olsson's picture

Available PhD position at the Division of Mechanics at Lund University

The Division of Mechanics at Lund University, Sweden, invites highly motivated and creative applicants for a PhD position oriented towards multiscale modelling of yielding and failure of materials subjected to harsh conditions in energy applications (e.g. components in fusion reactors, battery components, etc.).

Haoran Wang's picture

Modeling Uncertainties in Molecular Dynamics Simulations Using A Stochastic Reduced-Order Basis

We've recently published our new study about Uncertainty Quantification in Molecular Dynamics (MD) Simulations. Due to the selection of functional forms of interatomic potentials or the numerical approximation, MD simulations may predict different material behavior from experiments or other high-fidelity results. In this study, we used Stochastic Reduced Order Modeling (SROM) to achieve

(1) mechanical behavior of graphene predicted by MD simulations in good agreement with the continuum model which has been calibrated by experiments;

Nuwan Dewapriya's picture

Performing Uniaxial Tensile Tests of Graphene in LAMMPS

I would like to share the codes required to perform an end-to-end molecular dynamics simulation, which will be useful to the novice researchers in the filed of atomistic simulations. I focus on simulating uniaxial tensile tests of a graphene sample in the LAMMPS molecular dynamics simulator, and I have attached two MATLAB scripts to create the input files for LAMMPS and to extract data from the LAMMPS output file.

Jingjie Yeo's picture

Carbon nanotube arrays as multilayer transverse flow carbon nanotube membrane for efficient desalination

https://doi.org/10.1016/j.memsci.2019.03.062 This work presents the multilayer transverse flow carbon nanotube (CNT) membrane (TFCM), which resembles vertically aligned CNT arrays, as an alternative candidate for efficient desalination. Using molecular dynamics, this work shows that multilayer TFCM can provide permeability and salt rejection on par with its single layer counterpart.

Kmomeni's picture

PhD Positions in Multiscale Modeling of Materials Under Extreme Conditions

PhD positions are open immediately in Advanced Hierarchical Materials by Design Labat Louisiana Tech Universityon multiscale modeling of materials under extreme conditions. This will be a collaborative project with MITGeorgia Tech, and Idaho National Labthat is supported by Department of Energy.  The candidates must have earned a degree in Mechanical Engineering or related fields (applicants with a MSc will be given priority) and have a solid background in theoretical and computational mechanics.

Jingjie Yeo's picture

Multiscale Design of Graphyne‐Based Materials for High‐Performance Separation Membranes

https://doi.org/10.1002/adma.201805665 Computational modeling and simulations play an integral role in the bottom‐up design and characterization of graph‐n‐yne materials. Here, the state of the art in modeling α‐, β‐, γ‐, δ‐, and 6,6,12‐graphyne nanosheets for synthesizing graph‐2‐yne materials and 3D architectures thereof is discussed.

Kmomeni's picture

PhD position in Multiscale Modeling Materials Under extreme conditions

An immediate fully-funded Ph.D. position is open in Advanced Hierarchical Materials by Design Lab at Louisiana Tech University on multiscale modeling of materials under extreme conditions. The project involves collaboration with the computational research groups at national labs, as well as experimental researchers from MIT and Georgia Tech to test and validate the models and codes.

Kmomeni's picture

Two PhD Positions in Multiscale Modeling of Materials Under Extreme Conditions

Two PhD positions are open for Spring 2019 in Advanced Hierarchical Materials by Design Labat Louisiana Tech Universityon multiscale modeling of materials under extreme conditions. The candidates must have earned a degree in Mechanical Engineering or related fields (applicants with a MSc will be given priority) and have a solid background in theoretical and computational mechanics. Having knowledge of continuum mechanics, finite element modeling, and a programming language (preferably C++) is a plus. 

Jingjie Yeo's picture

Multiscale Modeling of Silk and Silk‐Based Biomaterials—A Review

https://doi.org/10.1002/mabi.201800253 In celebration of Stern Family Professor of Engineering David L. Kaplan, on the occasion of his 65th birthday, we review a selection of relevant contributions of computational modeling to understand the properties of natural silk, and to the design of silk-based materials, especially combined with experimental methods.

Jingjie Yeo's picture

Silica Aerogels: A Review of Molecular Dynamics Modelling and Characterization of the Structural, Thermal, and Mechanical Properties

https://doi.org/10.1007/978-3-319-50257-1_83-1 The second volume of the Handbook of Materials Modeling is now online: We reviewed the development of new empirical molecular dynamics forcefields, novel methods of generating aerogels’ percolated backbones, and compelling algorithms for characterizing their structural, mechanical, and thermal

Jingjie Yeo's picture

Effects of CNT size on the desalination performance of an outer-wall CNT slit membrane

https://doi.org/10.1039/C8CP01191E We investigate the effect of varying carbon nanotube (CNT) size on the desalination performance through slit confinements formed by horizontally aligned CNTs stacked on top of one another. By increasing the CNT size, the results obtained from this study indicate a corresponding increase in the water flow rate, accompanied by a slight reduction in salt rejection performance.

Wenjie Xia's picture

PhD positions in multiscale modeling of materials at North Dakota State University

One or two fully funded PhD positisons (tuition plus reasearch or teaching assistantships) are immediately available in the Computational Dynamics and Materials Laboratory at North Dakota State University (NDSU) during the academic year 2018~2019.

Jingjie Yeo's picture

Effects of oscillating pressure on desalination performance of transverse flow CNT membrane

https://doi.org/10.1016/j.desal.2018.03.029 In parallel with recent developments in carbon nanomaterials, there is growing interest in using these nanomaterials for desalination. To date, many studies have affirmed the potential of using such nanomaterials for constant pressure desalination operation. In this work, the performance of such membrane when subjected to oscillatory pressure at sub-nanosecond is investigated in detail.

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