Computational materials for energy and sustainability

Project Description:

We have a number of research topics available to choose from surrounding the theme of energy materials and biopolymers, including the structure-property relationship of bio-polymers, understanding exotic behaviors of solid-state ionics, solid materials, and interfaces for next-generation batteries, carbon magnets, and electronics, as well as applications of charged atomic clusters and molecules. The research methods we are using are computational and modeling, including state-of-the-art quantum mechanics calculations, molecular dynamics simulations, and machine learning techniques. Students will have the opportunity to participate in the ongoing research programs supported by the U.S. Department of Energy, with abundant resources featuring the most updated computing software and CPU/GPU nodes at national facilities. You will conduct computational research in advanced materials applied to energy storage and sustainability. You will learn in-demand skills of data analysis, machine learning, and Python programming. Students will also have opportunities to publish in high-impact journals and to collaborate with established research groups and institutes.

Requirements

Completed basic STEM courses; basic skills in programming, especially with Python.

Keywords/Areas of Study 

biomaterials, energy materials, batteries, modeling, data analysis, machine learning

Hourly Time Commitment (per week)

No fewer than 5 hours

Length of Commitment

Fall/Spring Semester

Start Date

Ongoing

Modality

Hybrid

Type of Opportunity

• Credit- or course-based (e.g., independent study, capstone project)
• Paid (e.g., Federal Work Study, funded research assistant)
• Volunteer (e.g., research assistant)

Contact Faculty Lead

Hong Fang
Department of Physics and the Center for Computational and Integrative Biology
Contact: hong.fang@rutgers.edu

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