Current research thrustsOur group's research focuses on understanding the processing-structure-property relationships in functional materials. Specifically, we pursue the following research thrusts, which enable the next generation of micro and nano-electro-chemo-mechanical devices.
Electromechanically-Active Materials We probe the fundamental science of ferroic materials, as it pertains to the mechanisms of intrinsic and extrinsic contributions to the functional response of these materials. Specifically, we probe the defect-defect interactions between domain walls, point, line and area defects. We also explore novel mechanisms and new processing approaches for enhanced electromechanical response at the micro and nanoscale (increased or invariant response with decreasing size). Of special interest are exploration of new material composition unstable in bulk form, understanding of the mesoscale origins of the giant electromechanical response in relaxor-ferroelectric solid solutions, radiation effects on the functional response of ferroelectric materials, and design of compositions for high energy storage applications. Correlation of the micro- and macro-scopic responses are other areas of interest within this research thrust. In-Situ and Operando Characterization at the Mesoscale This thrust hinges on design of energy discovery platforms: appropriately created micro- and nano-structures to enable in-situ and operando characterization at multiple length scales (e.g. piezoresponse force microscopy and electron microscopy, as well as macro-scale characterization techniques), while resulting in enhanced compatibility with mathematical and finite element modeling of the same. The coupled theoretical and experimental results allow a unique vision into the electro-chemo-mechanical processes with an unprecedented resolution (from tens of nanometers to few microns) over many orders of magnitude overall length-scales (tens to hundreds of microns). Specifically, we leverage machine learning approaches to separate physical and chemical contributors and understand correlation across properties and length scales in materials. Data Science Applications to Materials Science One of the biggest challenges in materials science and engineering remains the long lab-to-fab timelines, which is more and more often affected by claims unsubstantiated by the needed materials characterization since its conception or “discovery” in a laboratory. We attempt to reduce the lab-to-fab timeline in different fields of materials science through data science with a multi-pronged approach. 1) We leverage high-throughout characterization methods at multiple length scales that enable us to get better insights into the properties of materials even when large number of samples are not available for creating statistical analysis; 2) We collaborate with data scientists and signal processing experts to enhance our understanding of signal development in nanoscale characterization methods, with the goal of reducing controversies in data interpretation in literature. 3) We have direct collaboration with theory and modeling colleagues to design materials with desired functionalities. Far-from-Equilibrium Processing Approaches We explore new processing approaches for fabrication of micro and nanoscale complex oxide materials, with special focus on enabling technologies for fabrication of micro- and nano-electromechanical systems (MEMS and NEMS), and increased compatibility with CMOS processing for full integration and final miniaturization. These processing approaches are far-from-equilibrium and therefore result not only in substantially microstructure changes but also large variations of the final functional properties of the material. We probe the resulting properties of the materials, specifically targeting the physics of these complex oxides at the mesoscale, through integration of macro and microscopic characterization techniques. Our final goal is to create a processing design space that is uniquely correlated with the desired final functional responses. |
Current openingsSpring-Summer 2025 - filled
Undergraduate researcher(s) The SMART Lab at Georgia Tech has openings for multiple Undergraduate Research Assistants (URAs) working on machine learning approaches applied to understanding the nanoscale electromechanical response in materials. The ideal candidate would have a knowledge of signal processing and/or have some familiarity with data processing software such as Python, MATLAB, etc. Ability to commit for at least two semesters of research is preferred (first semester for credit, second semester for pay based on quality of performance during first semester). Graduate Researcher(s) We have an opening in the group for at least one doctoral graduate student working on 1) machine learning application to characterization of electro-chemo-mechanically active materials at the nanoscale and composition-structure-properties correlations in functional materials; 2) antiferroelectric thin films: design of properties through solid solutions and crystal anisotropy Others If you have secured your own funding (through industrial, private or governmental agencies), please mention this clearly in your application. If interested, please contract Prof. Bassiri-Gharb directly. In all cases, please mention the keyword watermelon in your emails. Specific areas of interest include:
Antiferroelectric, Ferrielectric, Ferroelectric, Relaxor and Relaxor-Ferroelectric Thin Films and Bulk Single CrystalsProcessing-structure-property relationships;
Machine learning application to characterization of functional materials; Chemical solution processing based thin film texturing; Defect-defect interactions; Irradiation effects; Beyond PZT: alternative compositions for high electromechanical coupling in thin films; Mesoscale development of the functional response in complex systems. Complex Oxide Micro/NanostructuresNovel processing techniques and CMOS compatibility;
Ferroic phenomena in confined geometries; In-situ studies of chemo-electro-mechanical functionality in oxide materials; Micro/Nano Solid-Oxide architectures and functional devices, e.g. micro-Fuel Cells (SOFCs). Flexoelectric Micro/NanoStructuresPatterned dielectric (para- and ferro-electric) thin films;
Flexoelectric materials for energy harvesting; Geometrical confinement and flexoelectricity. Multifunctional MaterialsSemiconductor, ferroic, photovoltaic, and quantum materials;
Strain-coupled thin films and nanostructures; Film texture and interfacial strain control in thin films. |
