Events

The widespread adoption of thermoset nanocomposites has created significant end-of-life management challenges due to their permanent crosslinked networks, which resist conventional recycling methods and trap valuable nanomaterials within non-degradable matrices. This work presents a proof-of-concept study to assess a new approach for achieving a circular economy for thermoset nanocomposites; recovering and reusing nanomaterials from thermoset nanocomposites through the incorporation of cleavable comonomers into the polymer matrix, enabling controlled matrix degradation and nanofiller recovery at end-of-life.

Carbon nanotubes (CNTs) were selected as the nanofiller for this study due to their widespread use in nanocomposites and growing industrial significance, and a styrene/divinylbenzene (DVB) thermoset matrix was chosen as a model matrix for its chemical compatibility with CNTs. To enable controlled degradation at end-of-life and nanofiller recovery, comonomer additives that can install cleavable bonds into the matrix’s polymer network were systematically evaluated. Several candidates were investigated, including cyclic ketene acetal (CKA) (specifically 2-methylene-1,3-dioxepane, MDO), which underwent hydrolysis too rapidly and an unwanted ring-retaining side reaction for practical application, and thionolactones (specifically dibenzo[c,e]-oxepine-5(7H)-thione, DOT and 2-(isopropylthio)dibenzo[c,e]oxepine-5(7H)-thione, 2SiPrDOT), which was limited by the monomers’ solubility in the styrene/DVB system. Through this careful screening process, 2SiPrDOT was selected as the most suitable option, offering both chemical stability during processing and sufficient solubility in the system.

Influence of Cellulose Nanocrystals and Surfactants on Catastrophic Phase Inversion and Stability of Emulsions

Atomistic Modelling and ReaxFF Parameter Optimization for Ionic Liquid Electrolyte

The Chemical Engineering Department is hosting a special graduate lecture on Optimizing Experiments: From Data-Driven to Intrusive Model-Based Methods. 

Battery Workforce Challenge party

Thesis Title: Transport and Irreversible Retention of Hydrophobic Nanoparticles by Fluid-Fluid and Fluid-Solid Interfaces in Porous Media

Abstract:

Hydrophobic nanoparticle (NP) transport in porous media has implications for aquifer transport and retention of a wide range of contaminants that infiltrate water resources and threaten human health as well as aquatic environments. Comprehension of NP transport and interactions with hydrophobic surfaces and interfaces -given their ubiquity in porous aquifers- is essential for groundwater remediation from organic contaminants, toxic engineered NPs, and nanoplastics.

This research investigates the transport and attachment of hydrophobic NPs under varying physicochemical conditions in saturated and unsaturated porous media by integrating experimental observations across multiple scales, theoretical extended-DLVO predictions, and numerical modeling. A non-toxic, negatively-charged, hydrophobic model NP system synthesized from ethyl cellulose (EC), and exhaustively characterized for colloidal stability and interfacial interactions, was employed to systematically explore NP interactions with fluid-fluid and solid-fluid interfaces.

The upscaling capability of an advection-dispersion-retention continuum model was compared vis-à-vis a pore network model of irreversible NP attachment onto fluid interfaces in 3D columns packed with spherical glass beads, showing that the latter captures key pore-scale dynamics such as bypassed interfaces, slow-moving corner flows, and diffusion-dominated retention.

Transport experiments in 2D microfluidic pore networks confirm that the dynamics of NP retention in unsaturated porous media depend not only on the saturation of the non-wetting phase, but also on its connectivity and the accessibility of immobile fluid-fluid interfaces.

Please find attached the invitation with our new date, Thursday, Feb. 5^th. All are welcome but you must register to attend!

Even if you had previously registered, you must re-register, so we know how much delicious pizza we need to order for the new party date.

Hope to see you there!

Hard Constrained Neural Networks for Process Systems Engineering Applications

Pervaporation Separation of Heteroaromatic Organic Compounds from Coking Wastewater Using PEBA-2533 Membranes

The Chemical Engineering Department is hosting a special graduate lecture on Optimization and simulation-based approaches to manage logistics of trucks and ships in large supply chains.