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Revolutionizing Materials Design with Computational Modeling

Material scientists at BU use computers housed at the MGHPCC as they seek to understand and predict functional material properties using first-principles electronic structure methods.

The Sharifzadeh Group at Boston University uses computational modeling to understand and predict the electronic and optical properties of materials, with applications in energy conversion, electronics, and nanotechnology. The group specializes in first-principles quantum mechanical simulations, which allow for the exploration of complex materials at the atomic and electronic levels without relying on experimental data. These simulations provide critical insights into how materials behave under different conditions, enabling the design of new materials with tailored properties for specific applications.

A key focus of the Sharifzadeh Group’s research is the study of organic and inorganic semiconductors, which are crucial for developing next-generation solar cells, light-emitting diodes (LEDs), and transistors. The group uses advanced density functional theory (DFT) and many-body perturbation theory (MBPT) techniques to model how electrons interact in these materials, predicting their conductivity, exciton dynamics, and energy band structures.

The group also investigates two-dimensional (2D) materials, such as graphene and transition metal dichalcogenides, which hold promise for use in flexible electronics and energy storage. By simulating these materials’ unique electronic and optical properties, the Sharifzadeh Group aims to uncover fundamental design principles that can guide experimental research and accelerate the development of new technologies for energy-efficient devices and materials.

Sahar Sharifzadeh
Associate Professor, Boston University

Research projects

Foldit
Dusty With a Chance of Star Formation
Checking the Medicine Cabinet to Interrupt COVID-19 at the Molecular Level
Not Too Hot, Not Too Cold But Still, Is It Just Right?​
Smashing Discoveries​
Microbiome Pattern Hunting
Modeling the Air we Breathe
Exploring Phytoplankton Diversity
The Computer Will See You Now
Computing the Toll of Trapped Diamondback Terrapins
Edging Towards a Greener Future
Physics-driven Drug Discovery
Modeling Plasma-Surface Interactions
Sensing Subduction Zones
Neural Networks & Earthquakes
Small Stars, Smaller Planets, Big Computing
Data Visualization using Climate Reanalyzer
Getting to Grips with Glassy Materials
Modeling Molecular Engines
Forest Mapping: When the Budworms come to Dinner
Exploring Thermoelectric Behavior at the Nanoscale
The Trickiness of Talking to Computers
A Genomic Take on Geobiology
From Grass to Gas
Teaching Computers to Identify Odors
From Games to Brains
The Trouble with Turbulence
A New Twist
A Little Bit of This… A Little Bit of That..
Looking Like an Alien!
Locking Up Computing
Modeling Supernovae
Sound Solution
Lessons in a Virtual Test Tube​
Crack Computing
Automated Real-time Medical Imaging Analysis
Towards a Smarter Greener Grid
Heading Off Head Blight
Organic Light-Harvesting Antennae
Art and AI
Excited by Photons
Tapping into an Ocean of Data
Computing Global Change
Star Power
Engineering the Human Microbiome
Computing Social Capital
Computers Diagnosing Disease
A Future of Unmanned Aerial Vehicles
Yale Budget Lab
Wearable Health Technology
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
The Rhode Island Coastal Hazards Analysis, Modeling, and Prediction System
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute – Unlocking Intelligence
The Institute for Experiential AI
The Forensic Video Exploitation and Analysis (FOVEA) Tool Suite
The Center for Scientific Computing and Data Science Research (CSCDR)
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer – Sequence Evaluation in Realtime
Sensorimotor Technology Realization in Immersive Virtual Environments (STRIVE)
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
Refugee Migration and Return on Social Media
QuEra at the MGHPCC
Predicting Reaction Barrier Heights
Quantum Computing in Renewable Energy Development
Quantifying Risk, Resilience, and Uncertainty with Machine Learning and HPC
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
Predicting Kinetic Solvent Effects
OpenCilk
Offshore Precipitation Capability (OPC) System
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
NASA Arctic-Boreal Vulnerability Experiment (ABoVE)
Monte Carlo eXtreme (MCX) – a Physically-Accurate Photon Simulator
Modeling Molecular Dynamics for Drug Delivery
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Machine Learning and Wastewater
Lichtman Lab – Center for Brain Science
Measuring Neutrino Mass
Learning-Task Informed Abstractions
Large-Scale Brain Mapping
Invisible Tags
Investigating Mantle Flow Through Analyses of Earthquake Wave Propagation
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Fuzzing the Linux Kernel
FlyNet
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
ElectroVoxels: Modular Self-reconfigurable Robots
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Collaborative projects

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Outreach & Education Projects

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