MSE Department Seminar

The emerging of new materials design tools and approaches, such as Materials Genome, machine learning and AI-assisted designs, are bringing new opportunities to materials science and engineering research. These new progresses also call for new experimental methodologies that can quickly verify and complement the computations/modeling. In our recent works, multiple in situ characterization methods were developed and combined with first principles based computations to design and develop new materials for energy storage in a significantly accelerated pace.

Globally, significant resources are consumed by the seemingly disparate challenges of controlling metal deposition, electrocatalysis, and corrosion. These problems seem particularly unrelated when considering their differing economic drivers and technical needs. However, despite the specific differences between these challenges, all of them are fundamentally driven by the same need for prediction and control of electron and ion transfer reactions at charged, heterogeneous interfaces.

Research into the mechanical behavior of brittle materials reached its height in the 1970’s and early 80’s. With notable exceptions, like RPI, many mechanics research laboratories have moved on to other areas of interest. For Corning Incorporated the need for mechanics knowledge has always been high and now more than ever. This talk will review some of the impactful mechanics work originating from the Mechanics Research Lab at Corning’s Sullivan Park technology center.

Coupling polymeric systems to nonlinear dynamics offers opportunities to create materials with tailored morphology and functionality via pattern forming processes. Examples include periodic striations from traveling fronts in thermal polymerization, coalescence of polymer films during dewetting, oscillatory gels, and phase separation. Here, we present a fundamentally new mechanism to organize polymeric materials that couples photopolymerization to the nonlinear dynamics of optical fields.

The need for higher efficiencies and performance in gas-turbine engines that propel aircraft in the air, and generate ~20% of world’s electricity on land, is pushing the engine operating temperatures to unprecedented levels. Replacing some of the current hot-section metallic components, coated with thermal-barrier coatings (TBCs), with ceramic-matrix composites (CMCs) is making that possible. A different type of high-temperature ceramic coatings system, that includes environmental-barrier coatings (EBCs), is needed to protect CMCs.

The discovery intrinsic magnetism in monolayer CrI3 and bilayer Cr2 Ge2Te6 created great interest in two-dimensional (2D) materials with intrinsic magnetic order. How many of these materials exist? What are their properties? We present a study of 2D materials with intrinsic magnetic order, materials at the forefront of physics research. We use materials informatics (machine learning applied to materials science) to study the magnetic and thermodynamic properties of 2D materials.

The synergy between the smart materials – power source – self-powered systems has provided the paradigm of “self-sustainable component and systems” for innovation driving the emergence of efficient and high-performance architectures. There is significant reduction in size and weight of the self-sustainable architectures as compared to traditional “grid-powered” or battery-powered devices. Some examples illustrating these self-sustainable architectures will be provided in this presentation covering solar, thermal, magnetic field and vibration energy harvesting.

Conductive polymer composites have been developed for electrostatic discharge and electromagnetic interference shielding. Loadings of >10% conductive fillers are typically required, but such loading levels result in high melt viscosity, poor appearance, contamination by sloughed off fillers and high material cost. We have found that small amounts of graphene nanoplatelets, 0.06 wt%, if located at the interfaces in a cocontinuous polymer blend, can percolate resulting in useful conductive composites.

In small enough semiconductor devices, the electron mean free path for collisions with impurities or lattice vibrations greatly exceeds the device size. Hence, the electrons travelling with the thermal or Fermi velocity leave the active region of the device before they experience scattering. Such collisionless electron transport is called “ballistic”. The electron mean free path in silicon at room temperature is on the order of 30 nm. This is much greater than the 7 or 10 nm feature size of modern silicon CMOS used, for example, in the recent generations of iPhones or android phones.

This lecture will detail the creation of ultrasensitive sensors based on carbon nanotubes (CNTs).  A central concept that a single nano- or molecular-wire spanning between two electrodes would create an exceptional sensor if binding of a molecule of interest to it would block all electronic transport. Nanowire networks of CNTs provide for a practical approximation to the single nanowire scheme.