Computational Materials Science
For several decades, many have dreamed that computational models based upon the theories of molecular dynamics or quantum mechanics would enable the prediction and modification of fundamental materials properties. But only in the last decade has this dream started to be realized. Our computational materials science group at Duke group is a leader in this effort.
Computational materials science research in the Department of Mechanical Engineering and Materials Science focuses on:
- Computational materials
- Electronic materials
- Solid state engineering
- Solid state physics
- Nanoscience and technology
- Optical properties of nanomaterials
- Advanced optics
- Thermodynamics of materials
Opportunities for Graduate Study
The department offers an M.S./Ph.D. with a study track in materials science and a core in solid materials and photonics. The course options emphasize nanoscience, nanomaterials and technology; photonics, solid state physics and electronic materials.
The department also offers a Master of Engineering (MEng) with an emphasis in materials science and engineering. This 30-credit degree program includes course work towards departmental requirements, an area of specialization, business and management fundamentals, and an internship or applied research experience. Students have the flexibility to focus on topics of solid, soft, bio and polymeric materials and characterization relevant to career preparation for the industrial sector.
Professor in the Department of Civil and Environmental Engineering
Research Interests: Computational mechanics, finite element methods, computational inverse problems and their applications in engineering and biomedicine, scientific computing, computational acoustics and acoustics-structure interaction, coupled chemo-mechanics (e.g. electrochemistry-mechanics).
Associate Professor of Mechanical Engineering & Materials Science (beginning July 1, 2017)
Research Interests: Computational methods to provide fundamental, molecular-level understanding of biological and material systems, with the aim of discovering new phenomena and developing new materials and technologies. The methods we use or develop are largely based on statistical mechanics, molecular modeling and...
Associate Professor in the Department of Mechanical Engineering and Materials Science
Research Interests: Computational predictions and understanding of new materials related to energy and electronics, as well as molecular structure and spectroscopies, based on the "first principles" of quantum mechanics. Much of this work is directly connected to ongoing developments of new algorithms and...
Professor in the Department of Mechanical Engineering and Materials Science
Research Interests: Nanoscale science of energy, computational materials science, nanotube growth characterization, alloy theory, superlubricity on quasicrystals, superconductivity in metal borides, genetic approaches to QM predictions of materials structures, materials for nuclear detection. His multidisciplinary...
Associate Professor of Mechanical Engineering and Materials Science
Research Interests: Olivier Delaire is an expert in the field of atomic dynamics in materials, with 15-plus years of experience in both experimental and computational studies of lattice dynamics (phonons).
Professor of Civil and Environmental Engineering
Research Interests: Modeling quasi-static and dynamic fracture of structural components, the evolution of interfaces with nonlinear constitutive laws, and developing models for stimulus-responsive hydrogels
Associate Professor in the Department of Civil and Environmental Engineering
Research Interests: Finite element methods, computational fluid and solid mechanics, multiphase porous media flows, computational methods for fluid and solid materials under extreme load conditions, turbulent flow computations, instability phenomena.
Assistant Research Professor in the Department of Mechanical Engineering and Materials Science
Research Interests: Computational materials science, with a focus on the development of high-throughput computational materials design frameworks such as AFLOW (Automatic FLOW).