Seminar Series

Bottom-up Biology: Building Synthetic Cells. Details TBA.

Intelligent Dental Implants. Details TBA.

Scientific Machine Learning in Biophysics and Materials. Details TBA.

An Overview of the DOE EFRC Mechano-chemical Understanding of Solid Ion Conductors (MUSIC). Details TBA.

Peng Chen is currently a tenure-track assistant professor in the School of Computational Science and Engineering at Georgia Tech. In this talk, he will present a novel machine learning framework for solving optimization problems governed by large-scale partial differential equations (PDEs) with high-dimensional random parameters.

Inspiration from nature has produced some fascinating, novel, and life changing solutions for the human world. Most of these bio-inspired designs however have been product based, but taking a systems perspective when we look to nature taps inspirations that can improve the critical networks we depend on. This talk focuses on biological ecosystems in particular, complex networks of interacting species that are able to support individual needs while maintaining system-level functions during both times of abundance and unexpected disturbances.

Ocean alkalinity enhancement (OAE) is a specific ocean CDR approach that can locally reverse ocean acidification and draw additional CO2 from the air into oceanic bicarbonate where it is stored for over10,000 years, mimicking the Earth’s natural mechanism for regulating the atmospheric CO2 concentration. In this talk, I will review the latest results from my group on electrochemical ocean alkalinity enhancement and describe the efforts to commercialize this technology at Ebb Carbon, Inc.

To create metallic scaffolds or microlattices with sub-millimeter strut architectures, we develop a new method, Extrusion 3D-Printing, consisting of two simple steps. First, metal oxide particle suspensions (inks) are extruded, in air and at ambient temperature, into linear struts creating self-supporting lattices. Second, the oxides are hydrogen-reduced to metal and sintered into dense metallic microlattices.

Fluid flows often exhibit chaotic or turbulent dynamics and require a large number of degrees of freedom for accurate simulation. Nevertheless, because of the fast damping of small scales by viscosity, these flows can in principle be characterized with a much smaller number of dimensions, as their long-time dynamics relax in state space to a finite-dimensional invariant manifold.

Physico-chemical interactions at interfaces are ubiquitous in multiple industries including energy, water, agriculture, medicine, transportation, and consumer products. In this talk, Kripa will summarize how surface/interface chemistry, morphology, thermal, and electrical properties can be engineered across multiple length scales for significant efficiency enhancements in a wide range of processes.

Vikas will present his team's theoretical framework and a microstructural physics-motivated constitutive model that describes the nonlinear large strain elastic-viscoplastic material response, rate-dependent stiffening and material state transformation of reversible dynamically crosslinked soft polymers over seven decades of strain rates.

The diversity and complexity of natural substrates—from flowable materials like sand and mud to steeply sloped tree branches and trunks with vast differences in flexibility and roughness—present significant challenges for animal movement.