Objective: Harness nanocellulose derived from Mexican biomass to produce 3D printable material for removing contaminants from water or air

Project summary: Cellulose nanogels derived from waste lignocellulosic biomass have emerged as a sustainable source material for numerous applications. We will explore their use for removing organic and inorganic pollutants from water or air. An expedient, practical, and cost-effective method for fabricating highly porous structures for filtration or adsorption tasks is to use 3D printing. To 3D print highly adsorptive materials, bio-inks containing nanocellulose must be formulated such that their rheological properties ensure their 3D printability. For direct ink writing (DIW) 3D printing, the bio-inks should exhibit: shear thinning behavior such that at typical printing shear rates the ink has low viscosity; higher viscosities (> 1000 Pa∙s) at low shear rates; and homogeneous structure to avoid clogging of the printing nozzle. We will derive nanocellulose from locally sourced biowaste (such as from nopal, a cactus farmed in Nuevo Leon, Mexico (the state where CIMAV Monterrey is located)). The nanocellulose will be combined with rheological modifiers such as graphene oxide or starches. After identifying formulations which possess suitable rheological properties, we will 3D print prototypes to be used for removing heavy metals from water or for trapping particulate matter from air.

Role of the student: Synthesize nanocellulose from agave or nopal; characterize nanocellulose gels and composites with FTIR spectroscopy, SEM, X-ray photoelectron spectroscopy (XPS), and rheology; design prototypes using a CAD program; print using a DIW-type 3D printer.

Objective: Use stereolithography to 3D print a working prototype of a fog-harvesting collector

Project summary: Recently, the Nano & Micro Additive Manufacturing of Polymers and Composite Materials Laboratory (the “3DLab”) at CIMAV Monterrey developed a method to produce parahydrophobic surfaces (PHSs). PHSs are both very hydrophobic (with water contact angles greater than 150°) as well as highly adhesive to water. These properties give rise to what is known as the “petal effect” and is seen in nature on certain leaves and petals, on the wings of some butterflies and beetles, and on gecko feet. For this project, surfaces with cubic micropillars containing both micro- and nano-scale roughnesses will be produced using stereolithography with an accessible 3D printer (Formlabs 3D). Wettability of these surfaces can be controlled by altering the geometrical parameters (such as the height, H, and pitch, P, of the pillars) as well as the surface modification using, e.g., fluoroalkyl silane compounds or functionalized nanoparticles. Students working at CIMAV Monterrey will use this method of producing PHS with roughness on both the micro- and nano-scale to produce fog-collecting devices. Fog harvesting is one potential remedy to water scarcity, particularly in desert areas, and is a method used by nature (e.g., in certain cacti which collect fog in their spines and barbs). Students will design and print PHS with various geometric parameters (e.g., H, P) and measure the water collection rate.

Role of the student: Design prototypes using a program like Solid Works; characterize the photopolymerizable resin using contact angle measurements, scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy and rheology; use an SLA 3D printer to produce textured surfaces; measure water collection rates.

Objective: Use and refine microrheology and bulk rheology techniques to quantify the properties of nanocellulose materials to be used in 3D printing applications

Project summary: Microrheology encompasses a range of techniques which typically employ passive micron-sized colloidal particles to probe the material properties of a sample. In contrast to bulk rheological studies which use a rheometer, microrheological methods require only a few microliters of the material. Further, microrheology can be performed using standard optical microscopes, instruments more accessible to most researchers than rheometers. However, microrheology is typically less well suited to measuring the low frequency mechanical properties than bulk rheology performed with a rheometer. Additionally, microrheology may not accurately measure the properties of a material that is heterogeneous on length scales larger than the distances probed by a colloidal particle. Therefore, investigating a material with both microrheology and bulk rheology can be advantageous for (1) verifying results of the complementary methods and (2) extending the range of length and time scales probed. For this project, students will measure the rheological properties of nanocellulose gels and mixtures containing nanocellulose (provided by the researchers at CIMAV) using a variety of microrheology tools and bulk rheology. The microrheology tools will include using optical tweezers, single particle tracking, and differential dynamic microscopy. The results from these techniques will complement data acquired on a bulk stress-controlled rotational rheometer. The aims of this project are to (1) evaluate the performance of microrheology techniques including new techniques employing differential dynamic microscopy which we will refine and (2) robustly characterize the rheology of nanocellulose gels and fluids to help guide the development of this material for 3D printing applications by the team at CIMAV Monterrey.

Role of the student: Perform sample preparations and rheological measurements; refine new microrheology methods, including streamlining data analysis routines for processing video microscopy images.

Objective: Quantify the dynamics of active and anisotropic particles under the influence of a laser-induced external field

Project summary: In the previously described project, students will investigate the dynamics of spherical colloidal particles in different samples. While passive spherical particles are often used in soft matter studies, particles that are anisotropic in shape (1) are often able to act as rheological modifiers at a lower volume fraction than spheres, (2) better mimic the non-spherical geometry of particulates found in industrial and biological materials (i.e., cellulose nanofibrils), and (3) can be used to model liquid crystal phases. Additionally, in comparison to passive particles, active particles can be used to probe a wider range of non-equilibrium phenomena and to model biological systems. Therefore, in this project students will first synthesize anisotropic and active particles. Those particles will then be exposed to the random potential energy landscape described in the previous project. While numerous studies have examined active or self-propelled particles, fewer have studied such particles in complex environments. As in the previous project, students will quantify the dynamics from recording time series of images on an optical microscope. For this project, students will extend the image analysis methods of the previous project to account for a combination of rotational and translational motion and/or to account for a mixture of actively-driven ballistic motion and thermally-driven diffusive motion. In this project, a combination of experiments and computer simulations will be used to understand the main features of anisotropic particles interacting with a variety of laser-induced external potentials.

Role of the student: Synthesize anisotropic particles using salt aggregation and fractionation by centrifugation; synthesize active particles through sputtering to partially cover spherical particles with carbon; prepare samples of active particles (i.e., self-propelled colloids) by confining a suspension of half-carbon-covered particles between glass slides in solvents with a critical transition around 34 °C and heating the sample with a laser; employ single particle tracking and other image analysis methods to extract particle dynamics; perform computer simulations to compare to experimental results.

Objective: To determine the response of a colloidal dispersion under the action of an external field.

Project summary: In bulk and without external perturbations, a dilute suspension of colloidal particles will have a homogeneous spatial distribution and exhibit normal Brownian diffusion. However, external fields can lead to more complex spatial distributions and transport properties. In this project, to better understand the experimental studies performed at UGTO with colloidal particles in laser-induced complex potential energy landscapes and the experimental work at CIMAV-Monterrey with complex fluids under shear, we will run computer simulations of spherical colloidal particles subjected to varying external perturbations. To further bridge experiments and simulations, we will use the simulations to calculate computer-generated images like what one would acquire using an optical microscope, including realistic point spread functions and image noise, so that these generated images can be analyzed similarly to our experimental data with single particle tracking and differential dynamic microscopy methods. The goals of this project will be to (1) determine how the depth of potential energy wells in a randomly configured potential energy landscape affect the thermally-driven dynamics of colloidal particles; (2) determine how the strength of an externally imposed shear force affects the dynamics and structure of colloidal particles with attractive interactions; and (3) compare how well image processing methods to extract colloidal dynamics and structure perform on simulated images by comparing the output of these methods with the dynamics and structure determined directly from the simulations.

Role of the student: Perform Brownian dynamics and Monte Carlo simulations of colloidal particles in various energy landscapes using a computer cluster; determine mean squared displacements and displacement probability distributions from particle trajectories; simulate video microscopy data from simulation data using expected microscope point spread functions, and camera noise specifications; analyze computer simulated images in parallel with experimentally acquired images so that any artifacts and limitations of our image analysis methods can be identified and addressed.