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NCN Undergraduate Research Projects 2015

This page presents some of the research areas that NCN SURF students will have an opportunity to participate in. Projects available for Summer 2016 will be added by mid-December, 2015.  If you are interested in a particular area of research,  be sure to indicate your preference in your SURF application.


Nanoelectronics Modeling

Gerhard Klimeck

Professor Gerhard Klimeck, Electrical and Computer Engineering

nanoHUB is the home of an online community for scientific education and research related to nanotechnology. The iNEMO group, headed by Gerhard Klimeck, conducts research on nanoelectronics modeling. This includes a variety of areas such as next-generation transistor designs and materials, quantum computing, and advanced numerical algorithms. The cornerstone of this research is NEMO5, a multiphysics, multiscale software package developed by the iNEMO group. A core goal is to bring that nanoelectronics modeling capability to users' machines via easy-to-use nanoHUB web-based tools based on the NEMO5 engine.  

Desired Skills:  Students should have a background in materials, numerical algorithms, semiconductor device physics, optoelectronics or a related area and must have a desire to bring a viable product to fruition. Students will have the opportunity to learn about and use high-performance computing systems. Students will work under the supervision of a graduate student mentor but need to be able to problem-solve on their own as well.

Computer Language Used:  No specific programming language experience is required, but students should have some experience coding and more importantly, a desire to learn and conduct software development. nanoHUB has over 300,000 annual users and NEMO-powered tools are used by thousands of researchers and in hundreds of classes around the globe.

The nanoHUB tools developed in iNEMO include:

 


Computational Solid Mechanics

Marisol Koslowski

Professor Marisol Koslowski, Mechanical Engineering

Understanding the behavior of materials at the nano/micron scale furnishes the basis required to develop theoretical models and reliable numerical tools to predict the reliability of engineering devices.  Progress in electronic and optoelectronic technologies depends on the ability to synthesize  materials with the desired optical and electronic properties. These properties are very sensitive to structural defects generated during semiconductor growth. The effect of strain and the nucleation of defects during growth has proven to be of key importance.  

The goal of this project  is to develop a tool to predict the formation of misfit dislocations in semiconductor heterostructures.  

Desired skills:  Students should have a background in mechanical, optical and electrical properties of materials, knowledge of numerical algorithms and programing.


Nano-mechanical response of materials by molecular dynamics

David Johnson

Professor David Johnson, Materials Engineering

The goal of this project is to develop a simulation tool to predict the formation of misfit dislocations in semiconductor heterostructures. 

Understanding the behavior of materials at the nano/micron scale furnishes the basis to develop theoretical models and reliable numerical tools to predict the reliability of engineering devices.  Progress in electronic and optoelectronic technologies depends on the ability to synthesize  materials with the desired optical and electronic properties. These properties are very sensitive to structural defects generated during semiconductor growth. The effect of strain and the nucleation of defects during growth has proven to be of key importance.

The project will focus on development of simulation tools to study the mechanical response of materials at the atomic level for both research and education.  Interactive simulation tools will be developed to study the anisotropic elastic properties, deformation mechanisms, and fracture of crystalline solids using research-grade molecular dynamics (MD) codes.   The student will help develop the virtual nanostructures and testing procedures to simulate these structures as a function of loading geometry, strain rate and temperature.  The research includes exploring the relationships between bonding and elastic properties and between dislocation motion and crystalline plasticity.

Desired skills:  Students should have a background in mechanical, optical and electrical properties of materials, knowledge of numerical algorithms and programming.


Computational Fluid Dynamics

Simulation of Molecular Collisions and Transport in Reacting Non-Equilibrium Flows

Alina Alexeenko

Professor Alina Alexeenko, Aeronautics and Astronautics

The project will involve application of Quasi-Classical Trajectory calculations and direct simulation Monte Carlo to analyze molecular collisions and transport processes in nonequilibrium gases. Highly nonequilibrium flows in molecular regime are encountered in low-pressure environments, such as chemical vapor deposition, molecular beam epitaxy and other methods used for nanostructure manufacturing. Additional applications arise in gas-phase transport in N/MEMS.

Skills/qualifications: Coursework in fluid mechanics, numerical analysis, programming. The simulation codes are written in MATLAB and Fortran.

 

 


Predictive Materials Simulation

Alejandro H Strachan

Professor Alejandro Strachan, Materials Engineering

Our research focuses on the development of predictive atomistic and molecular simulation methodologies to describe materials from first principles, their application to problems of technological importance and quantification of associated uncertainties. Application areas of interest include: electronic, thermal and mechanical properties of nano- and micro-electromechanical systems and electronic and energy conversion devices; thermo-mechanical response of polymer composites and molecular solids; and physics and chemistry of active materials including shape memory and energetic materials.

 

 


 

Energy Applications

Nanophotonics to improve the performance of photovoltaic and thermophotovoltaic systems

Peter Bermel

Professor Peter Bermel, Electrical and Computer Engineering

Last year, 61% of raw energy consumption (e.g., coal combustion) was wasted as heat. Recapturing this waste heat could greatly reduce raw energy consumption to save money and reduce environmental impacts. There are several approaches to capturing waste heat, one of which is known as thermophotovoltaics (TPV). TPVs convert heat to electricity using thermal radiation to illuminate a photovoltaic (PV) diode. Typically, this radiation is generated by a blackbody-like emitter. The emitted photons can be captured by the PV diode to generate electricity. Furthermore, the temperature difference between emitter and receiver requires separation between the two, creating a gap in which more photons can be lost. Thus, introducing a selective emitter, filter, and waveguide to recycle unwanted photons could greatly enhance performance.

Overall research goals: In our nanoHUB SURF research, we will construct a GUI-based simulation tool to precisely calculate the details of how special emitters and waveguides can help improve the thermal spectrum and subsequent photon recycling. We will also consider the role of optical and electronic transport in the PV cell. Our tool will be hosted and run through nanoHUB.org - an open-access science gateway for cloud-based simulation tools and resources in nanoscale science and technology.

Minimum skills and knowledge: Familiarity with introductory mechanics and electromagnetism is required. A working ability to read and modify scientific code is also needed. Finally, the ability to quickly learn a new scientific topic is desired.

Additional, desirable skills and knowledge:  Knowledge of the drift-diffusion and heat diffusion equations for current and heat transport is a plus. An understanding of basic (first-quantized) quantum mechanics, including Schrodinger’s equation and time-independent and time-dependent first-order perturbation theory is a plus.

Computer language used: Python and MATLAB/Octave are preferred languages for nanoHUB coding. Working familiarity with Linux and shell scripts is also a plus.

 


Battery and Piezoelectric Systems

R. Edwin García

Professor Edwin Garcia, Materials Engineering

Simulating the Effect of Fabrication of Battery Materials on their Performance

This project aims to quantify the effect of the starting powders, binders, electrode thicknesses on the delivered power and energy density of Li-Ion Batteries. Through the use of 2D and 3D simulations and by combining real and computer-generated porous battery architectures, we will quantify which parameters experimentalists should be focusing on, and what architectures would be best ones.

Effect of Internal Particle Structure and Morphology on Battery Performance

Here, the focus is on understanding how the combined effect of the internal anisotropy of individual nanoparticles of active material and their external shape has an impact on the power and energy density response of the system. Through numerical simulation, we aim to understand how non-spherical shaped single-crystal particles  may delivered improved energy density.

Design of Separator Structures for Lithium-Ion Batteries

Separators are structures sandwiched between the cathode and anode layers in rechargeable batteries. Their stability, high conductivity, and malleability depends on the topology associated to its internal porosity. In this project, by using Monte Carlo and kinetic equations of motion we will identify those architectures that lead to improved performance.

Piezoelectric Materials for Energy Applications

Piezoelectric structures have been recently proposed as energy harvesting devices, where an external mechanical pressure generates charge that can be readily stored for later use. In this project, by using Finite Element modeling, we explore out-of-the-box configurations and thermal and chemical initial conditions that  will lead to improved piezoelectric actuation.


Mechanical Degradation Processes in Si Anodes of Li-ion Batteries

Guang Li

Professor Guang Lin, Mechanical Engineering and Mathematics

Overall goal: Study the mechanical degradation processes in Si anodes and design next-generation Si-anode based Li-ion batteries.

Motivation: Si anodes are a promising alternative for Li-ion batteries as Si has the largest specific capacity among all known anode materials. Nevertheless, in order to make Si anodes a reality there is a need to prevent the mechanical degradation of the anode due to the massive volume changes occurring upon Li insertion. In particular, in this project, we will use a meso-scale smoothed particle hydrodynamics (SPH) computational model to simulate the mass and charge transport in the porous anode structure at the anode. In addition, we will evaluate the thermal-mechanical damage due to fracture and interfacial delamination.

Desired skills:  Experience in MATLAB or C++ programming language, and computational modeling. The students will learn about how to model meso-scale physics in energy-storage devices during the summer.

Computer languages: MATLAB, C++

Required fundamental knowledge: Linear algebra and numerical methods for differential equations.

 


Manufacturing Processes

Microstructure evolution during powder compaction

Marcial Gonzalez

Professor Marcial Gonzalez, Mechanical Engineering

Overall goal: The goal of this project is to develop new, and improve current, capabilities for modeling, simulation and prediction of microstructure formation and evolution during the compaction of powders.

Motivation: Compaction of powders is a manufacturing process used in many industries. It consists of the synthesis of loose powders into solid bodies. Many materials need to be made (or can only be made) in the form of small particles. The final products made of these materials, however, need to be of macroscopic size. The performance of these final products is directly related to their microstructural features, thus the fundamental understanding of the compaction process becomes of paramount importance. Powder compaction is used in the pharmaceutical industry when the active pharmaceutical ingredient is crystallized in the form of micro- or nano-particles to improve in vivo bioavailability. Nano-powders are pressed into solids to achieve unique thermo-electric and mechanical properties needed for electronic, energy and aerospace applications.

Desirable skills: Experience in computational modeling of physical phenomena and manufacturing processes and basic knowledge of granular media behavior. Though previous experience is desirable, the student will learn about the unique physics of granular media and about powder compaction during the summer.

Computer language: MATLAB

Required fundamental knowledge: Basic knowledge about mechano-chemical properties of solid materials and linear algebra.

 

Web-based simulation of granular materials and nanoparticle self-assembly

Timothy S. Fisher

Professor Timothy Fisher, Mechanical Engineering

Overall goal: Understanding the physics of manufacturing heterogenous materials via the popular processes of granular jamming, colloidal gelation and nanoparticle self (or directed) assembly is crucial to designing tailored materials for functional applications such as energy devices (thermoelectrics, photovoltaics), bio-sensing and electrocatalysis. At sub-micron length scales, the interparticle interactions are complex and dominated by conservative (van der Waals and electrostatic) and entropic (polymer-mediated or depletion dictated by particle shape) forces. This project seeks the development of a consolidated, web-based suite of computational tools (to be hosted on nanoHUB) to simulate the aforementioned processes. We employ optimization routines to explore the free energy hyperspace and predict stable microstructures along with detailed geometric (incl. visual) and mechanical characterization. The availability of such tools (for rapid prototyping these materials) through an open-source hosting will be of great benefit to the researchers (experimental and computational) working in this field.

Expected Student Contributions: This project is primarily computational and will involve: a) object-oriented development (and extension) of existing prototype code for simulations, b) hosting the code on nanoHUB for a web-based interface, and c) exploring possible avenues for parallelization.

Desirable skills: Strong programming skills. Knowledge of MATLAB, C/C++ is required. Prior experience with object-oriented programming is highly desired. Willingness to learn the principles of soft condensed matter physics.


Design-optimization with a Limited Data-Budget

Ilias Bilionis

Professor Ilias Bilionis, Mechanical Engineering

Overall goal: Create a nanoHUB simulation tool that facilitates the design of products by suggesting to the user which experiments/simulations to perform in order to get as close as possible to the desired goal within a limited experimental/simulation budget.

Motivation: National laboratories, research groups, and corporate R&D departments have spent decades and billions of dollars to develop realistic computer models for a wide array of engineered systems. Typical examples include nuclear reactors, combustion engines, aircraft turbines, medicine, oil reservoirs, and many others. The driving force behind the development of these models has been their potential of being used to design systems with desirable properties. Unfortunately, directly using the full-fledged models in a usual design framework is computationally intractable (each simulation might take a month on a super-computer). The challenge is, How can you design a system with a limited data-acquisition budget?  This “data-budget” is related to the amount of money you can afford spend on experiments or on computer simulations.

Required skills:  Calculus (integrals, derivatives, multivariate functions), Linear algebra (matrices, linear systems), programming in Python.

Desired Skills:  Numerical computing in Python (numpy, scipy), Probability and statistics, Bayesian probability, Gaussian process regression, Utility theory, Numerical optimization, Information theory, Parallel computing in Python (mpi4py).


Materials Characterization

Electron Energy Loss Spectroscopy Simulations for Materials Research

Volkan Ortalan

Professor Volkan Ortalan, Materials Engineering

Overall research goals: In our nanoHUB SURF research, we will construct a GUI-based simulation tool for calculations of electron energy loss spectroscopy (EELS). EELS is the study of material properties through measurement of its energy absorption from an electron beam in a Transmission Electron Microscope (TEM). TEM gives information about the positions of the atoms and EELS provides information about the electronic structure and bonding of the material. We will also develop tools to facilitate the interactive data analysis of multidimensional datasets (also known as spectrum images) for extracting the signatures present in the spectra. Our tool will be hosted and run through nanoHUB.org.

Minimum skills and knowledge: Familiarity with electromagnetism, basic quantum mechanics and solid state physics is required. A working ability to read and modify scientific code is also needed.

Additional, desirable skills and knowledge:  Knowledge of fundamental principles of electron microscopy is a plus. An understanding of basic quantum mechanics, including Schrodinger's equation and density functional theory is a plus.

Computer language used: Python and MATLAB/Octave are preferred languages for nanoHUB coding. Working familiarity with Linux and shell scripts is also a plus.