Thiol Coordination Softens Liquid Metal Particles To Improve On-Demand Conductivity.

Achieving tunable rupturing of eutectic gallium indium (EGaIn) particles holds great significance in flexible electronic applications, particularly pressure sensors. We tune the mechanosensitivity of EGaIn particles by preparing them in toluene with thiol surfactants and demonstrate an improvement over typical preparations in ethanol. We observe, across multiple length scales, that thiol surfactants and the nonpolar solvent synergistically reduce the applied stress requirements for electromechanical actuation. At the nanoscale, dodecanethiol and propanethiol in toluene suppress gallium oxide growth, as characterized by transmission electron microscopy and X-ray photoelectron spectroscopy. Quantitative AFM imaging produces force-indentation curves and height images, while conductive AFM measures current while probing individual EGaIn particles. As the applied force increases, thiolated particles demonstrate intensified softening, rupturing, and stress-induced electrical activation at forces 40% lower than those for bare particles in ethanol. To confirm that thiolation facilitates rupturing at the macroscale, a laser is used to ablate samples of EGaIn particles. Scanning electron microscopy and resistance measurements across macroscopic samples confirm that thiolated EGaIn particles coalesce to exhibit electrical activation at 0.1 W. Particles prepared in ethanol, however, require 3 times higher laser power to demonstrate a similar behavior. This unique collection of advanced techniques demonstrates that our particle synthesis conditions can facilitate on-demand functionality to benefit electronic applications.

In situ polymer gelation in confined flow controls intermittent dynamics.

Polymer flows through pores, nozzles and other small channels govern engineered and naturally occurring dynamics in many processes, from 3D printing to oil recovery in the earth's subsurface to a wide variety of biological flows. The crosslinking of polymers can change their material properties dramatically, and it is advantageous to know a priori whether or not crosslinking polymers will lead to clogged channels or cessation of flow. In this study, we investigate the flow of a common biopolymer, alginate, while it undergoes crosslinking by the addition of a crosslinker, calcium, driven through a microfluidic channel at constant flow rate. We map the boundaries defining complete clogging and flow as a function of flow rate, polymer concentration, and crosslinker concentration. Interestingly, the boundaries of the dynamic behavior qualitatively match the thermodynamic jamming phase diagram of attractive colloidal particles. That is, polymer clogging occurs in a region analogous to colloids in a jammed state, while the polymer flows in regions corresponding to colloids in a liquid phase. However, between the dynamic regimes of complete clogging and unrestricted flow, we observe a remarkable phenomenon in which the crosslinked polymer intermittently clogs the channel. This pattern of deposition and removal of a crosslinked gel is simultaneously highly reproducible, long-lasting, and controllable by system parameters. Higher concentrations of polymer and cross-linker result in more frequent ablation, while gels formed at lower component concentrations ablate less frequently. Upon ablation, the eluted gel maintains its shape, resulting in micro-rods several hundred microns long. Our results suggest both rich dynamics of intermittent flows in crosslinking polymers and the ability to control them.

Mixing particle softness in a two-dimensional hopper: Particle rigidity and friction enable variable arch geometry to cause clogging.

Understanding the clogging of mixtures of soft and rigid particles flowing through hoppers becomes important as soft particle usage increases in consumer products. We investigate this clogging under varying particle size and rigid fraction by quantifying various properties of arches formed in the neck of a quasi-two-dimensional hopper. As more soft particles are added to the mixture, the arch tends to become both narrower and more curved. This effect arises from the fact that soft particles have less ability to sustain a clog than rigid particles. The clogging probability is seen to have a linear correlation with the span (width) of the arch. The angles between the arch particles are shown to have higher values as rigid fraction increases. The arch occasionally shows a partially convex shape at high rigid fractions when rigid particles are sitting next to each other, while soft particles can form angles of less than 180^{∘} only. The relation between the span and aspect ratio (width to height) of the arch is theoretically formulated for three-particle arches and extended to arches of more than three particles, using an asymptotic parameter that represents the width of a flat arch. Finally, it is concluded that clogging probability closely correlates with both the arch span and the variation of other geometric arch properties.

Application of droplet migration scaling behavior to microchannel flow measurements.

In confined channels in low Reynolds number flow, droplets drift perpendicular to the flow, moving across streamlines. The phenomenon has proven useful for understanding microfluidic droplet separation, drug delivery vehicle optimization, and single-cell genomic amplification. Particles or droplets undergo several migration mechanisms including wall migration, hydrodynamic diffusion, and migration down gradients of shear. In simple shear flow only wall migration and hydrodynamic diffusion are present. In parabolic flow, droplets also move down gradients of shear. The resulting separation depends on parameters including particle size and stiffness, concentration, and flow rate. Computational methods can incorporate these effects in an exact manner to predict margination phenomena for specific systems, but do not generate a descriptive parametric dependence. In this paper, we present a scaling model that elucidates the parametric dependence of margination on emulsion droplet size, volume fraction, shear rate and suspending fluid viscosity. We experimentally measure the droplet depletion layer of silicone oil droplets and compare the results to theoretical scaling behavior that includes hydrodynamic diffusion and wall migration with and without an added shear-gradient migration. Results demonstrate the viability and limitations of applying a simple scaling behavior to experimental systems to describe parametric dependence. Our conclusions open the possibility for parametric descriptions of migration with broad applicability to particle and droplet systems.

Flow dynamics through discontinuous clogs of rigid particles in tapered microchannels.

Suspended particles flowing through complex porous spaces exhibit clogging mechanisms determined by factors including their size, deformability, and the geometry of the confinement. This study describes the clogging of rigid particles in a microfluidic device made up of parallel microchannels that taper from the inlet to the outlet, where the constriction width is approximately equal to the particle size. This converging geometry summarizes the dynamics of clogging in flow channels with constrictions that narrow over multiple length scales. Our novel approach allows the investigation of suspension flow dynamics in confined systems where clogs are formed both by sieving and bridging mechanisms simultaneously. Here, flow tests are conducted at constant driving pressures for different particle volume fractions, and a power-law decay which appears to be peculiar to the channels' tapered geometry is observed in all cases. Compared to non-tapered channels, the power-law behavior shows flowrate decay is significantly weaker in tapered channels. This weaker flowrate decay is explained by the formation of discontinuous clogs within each channel. Micrographs of the clogged channels reveal clogs do not grow continuously from their initial positions around the channels' outlet. Rather, new clogs spanning the width of the channel at their points of inception are successively formed as the cake grows toward the inlet area in each microchannel. The results show changes in particle volume fraction at constant driving pressure affect the clogging rate without impacting the underlying dynamics. Unexpectedly, analyses of the particles packing behavior in the microchannels, and post-clogging permeability of the microfluidic devices, reveal the presence of two distinct regimes of driving pressure, though only a small portion of the total device volume and channels surface area are occupied by clogs, regardless of the particle volume fraction. This novel investigation of discontinuous clogging over multiple particle diameters provides unique insights into additional mechanisms to control flow losses in filtration and other confined systems.

Soft particles facilitate flow of rigid particles in a 2D hopper.

The flow of granular materials through narrow openings governs flow and process efficiency in a variety of industrial settings. As the use of soft particles and other soft micro-materials becomes more widespread in consumer products, we seek to understand characteristics of granular flows beyond powder flows. We study clogging through a 2D hopper in systems consisting of a combination of soft and rigid particles of different sizes and mixing fractions. Our experimental results show that soft particles play a lubricating role in the flow of rigid spheres due to their deformability and slick surface, but the size of rigid particles influences clogging more than the size of soft ones. We simulate our results using a modification of the Durian bubble model to accommodate mixtures of particles of different softness. Without any adjustable parameters, the simulation results capture the clogging probability of soft-rigid particle mixtures through a 2D hopper.

A Machine Learning and Computer Vision Approach to Rapidly Optimize Multiscale Droplet Generation.

Generating droplets from a continuous stream of fluid requires precise tuning of a device to find optimized control parameter conditions. It is analytically intractable to compute the necessary control parameter values of a droplet-generating device that produces optimized droplets. Furthermore, as the length scale of the fluid flow changes, the formation physics and optimized conditions that induce flow decomposition into droplets also change. Hence, a single proportional integral derivative controller is too inflexible to optimize devices of different length scales or different control parameters, while classification machine learning techniques take days to train and require millions of droplet images. Therefore, the question is posed, can a single method be created that universally optimizes multiple length-scale droplets using only a few data points and is faster than previous approaches? In this paper, a Bayesian optimization and computer vision feedback loop is designed to quickly and reliably discover the control parameter values that generate optimized droplets within different length-scale devices. This method is demonstrated to converge on optimum parameter values using 60 images in only 2.3 h, 30× faster than previous approaches. Model implementation is demonstrated for two different length-scale devices: a milliscale inkjet device and a microfluidics device.

Adapting Undergraduate Research to Remote Work to Increase Engagement.

Demand for undergraduate research experiences typically outstrips the available laboratory positions, which could have been exacerbated during the remote work conditions imposed by the SARS-CoV-2/COVID-19 pandemic. This report presents a collection of examples of how undergraduates have been engaged in research under pandemic work restrictions. Examples include a range of projects related to fluid dynamics, cancer biology, nanomedicine, circadian clocks, metabolic disease, catalysis, and environmental remediation. Adaptations were made that included partnerships between remote and in-person research students and students taking on more data analysis and literature surveys, as well as data mining, computational, and informatics projects. In many cases, these projects engaged students who otherwise would have worked in traditional bench research, as some previously had. Several examples of beneficial experiences are reported, such as the additional time spent studying the literature, which gave students a heightened sense of project ownership, and more opportunities to integrate feedback into writing and research. Additionally, the more intentional and regular communication necessitated by remote work proved beneficial for all team members. Finally, online seminars and conferences have made participation possible for many more students, especially those at predominantly undergraduate institutions. Participants aim to adopt these beneficial practices in our research groups even after pandemic restrictions end.

Relating Selectivity and Separation Performance of Lamellar Two-Dimensional Molybdenum Disulfide (MoS2) Membranes to Nanosheet Stacking Behavior.

Increased demand for highly selective and energy-efficient separations processes has stimulated substantial interest in emerging two-dimensional (2D) nanomaterials as a potential platform for next-generation membranes. However, persistently poor separation performance continues to hinder the viability of many novel 2D-nanosheet membranes in desalination applications. In this study, we examine the role of the lamellar structure of 2D membranes on their performance. Using self-fabricated molybdenum disulfide (MoS2) membranes as a platform, we show that the separation layer of 2D nanosheet frameworks not only fails to demonstrate water-salt selectivity but also exhibits low rejection toward dye molecules. Moreover, the MoS2 membranes possess a molecular weight cutoff comparable to its underlying porous support, implying negligible selectivity of the MoS2 layer. By tuning the nanochannel size through intercalation with amphiphilic molecules and analyzing mass transport in the lamellar structure using Monte Carlo simulations, we reveal that small imperfections in the stacking of MoS2 nanosheets result in the formation of catastrophic microporous defects. These defects lead to a precipitous reduction in the selectivity of the lamellar structure by negating the interlayer sieving mechanism that prevents the passage of large penetrants. Notably, the imperfect stacking of nanosheets in the MoS2 membrane was further verified using 2D X-ray diffraction measurements. We conclude that developing a well-controlled fabrication process, in which the lamellar structure can be carefully tuned, is critical to achieving defect-free and highly selective 2D desalination membranes.

Shape-Dependent Interactions of Manganese Oxide Nanomaterials with Lipid Bilayer Vesicles.

Interactions of transition-metal-oxide nanomaterials with biological membranes have important environmental implications and applications in ecotoxicity and life-cycle assessment analysis. In this study, we quantitatively assess the impact of MnO2 nanomaterial morphology-one-dimensional (1D) nanowires, 2D nanosheets, and 3D nanoflowers-on their interaction with phospholipid vesicles as a model for biological membranes. Confocal microscopy suggests visual evidence for the interaction of undisrupted vesicles with dispersed MnO2 nanomaterials of different morphologies, and it further supports the observation that minimal dye leakage of the vesicle inner solution was detected during the interaction with MnO2 nanomaterials during the dye leakage assay. Upon titration of vesicles to dispersions of MnO2 nanowires, nanosheets, and nanoflowers, each roughly 10 times larger than the vesicles, dynamic light scattering reveals two diffusive time scales associated with aggregates in the mixture. While the longer time scale corresponds to the dispersed MnO2 control population, the appearance of a shorter timescale with vesicle addition indicates interaction between the dispersed metal oxide nanomaterials and the vesicles. The interaction is shape-dependent, being more pronounced for MnO2 nanowires than for nanosheets and nanoflowers. Furthermore, the shorter diffusive time scale is intermediate between the vesicle and nanomaterial controls, which may suggest a degree of metal oxide aggregate breakup. Vesicle adsorption isotherms and zeta potential measurements during titration corroborate vesicle attachment on the nanomaterials. Our results suggest that the dispersed nanomaterial shape plays an important role in mediating nondestructive vesicle-nanomaterial interactions and that lipid vesicles act as efficient surfactants for MnO2 nanomaterials.

Establishing structure-property-hazard relationships for multi-walled carbon nanotubes: the role of aggregation, surface charge, and oxidative stress on embryonic zebrafish mortality.

Increasing use of carbon nanotubes (CNTs) in consumer and industrials goods increases their potential release, and subsequent risks to environmental and human health. Therefore, it is becoming ever more important that CNTs are designed to reduce or eliminate hazards and that hazard assessment methodologies are robust. Here, oxygen-functionalized multi-walled CNTs (O-MWCNTs), modified under varying redox conditions, were assessed for toxic potential using the zebrafish (Danio rerio) embryo model. Multiple physicochemical properties (e.g., MWCNT aggregate size, morphology, and rate; surface charge and oxygen concentration; and reactive oxygen species (ROS) generation) were characterized and related to zebrafish embryo mortality through the use of multivariate statistical methods. Of these properties, surface charge and aggregate morphology emerged as the greatest predictors of embryo mortality. Interestingly, ROS generation was not significantly correlated to observed mortality, contrary to prior predictions by nanotoxicology researchers. This suggests that the mechanism of MWCNT-induced mortality of embryonic zebrafish is physical, driven by electrostatic and shape effects, both of which are related to nanomaterial aggregation. This raises the importance of rigorously considering aggregation during aqueous-based nanotoxicology assays as nanomaterial aggregation can affect perceived nanomaterial toxicity. As such, future nanotoxicity studies relying on aqueous media must sufficiently consider nanomaterial aggregation.

Combined Organic Fouling and Inorganic Scaling in Reverse Osmosis: Role of Protein-Silica Interactions.

We investigated the relationship between silica scaling and protein fouling in reverse osmosis (RO). Flux decline caused by combined scaling and fouling was compared with those by individual scaling or fouling. Bovine serum albumin (BSA) and lysozyme (LYZ), two proteins with opposite charges at typical feedwater pH, were used as model protein foulants. Our results demonstrate that water flux decline was synergistically enhanced when silica and protein were both present in the feedwater. For example, flux decline after 500 min was far greater in combined silica scaling and BSA fouling experiments (55 ± 6% decline) than those caused by silica (11 ± 2% decline) or BSA (9 ± 1% decline) alone. Similar behavior was observed with silica and LYZ, suggesting that this synergistic effect was independent of protein charge. Membrane characterization by scanning electron microscopy and Fourier transform infrared spectroscopy revealed distinct foulant layers formed by BSA and LYZ in the presence of silica. A combination of dynamic light scattering, transmission electron microscopy , and energy dispersive X-ray spectroscopy analyses further suggested that BSA and LYZ facilitated the formation of aggregates with varied chemical compositions. As a result, BSA and LYZ were likely to play different roles in enhancing flux decline in combined scaling and fouling. Our study suggests that the coexistence of organic foulants, such as proteins, largely alters scaling behavior of silica, and that accurate prediction of RO performance requires careful consideration of foulant-scalant interactions.

Activatable Protein Nanoparticles for Targeted Delivery of Therapeutic Peptides.

Clinical translation of therapeutic peptides, particularly those that require penetration of the cell membrane or are cytolytic, is a major challenge. A novel approach based on a complementary mechanism, which has been widely used for guided synthesis of DNA or RNA nanoparticles, for de novo design of activatable protein nanoparticles (APNPs) for targeted delivery of therapeutic peptides is described. APNPs are formed through self-assembly of three independent polypeptides based on pairwise coiled-coil dimerization. They are capable of long circulation in the blood and can be engineered to target diseases. Peptides to be delivered are incorporated into APNPs and released into the disease microenvironment by locally enriched proteases. It is demonstrated that APNPs mediate efficient delivery of NR2B9c, a neuroprotective peptide that functions after cell penetration, and melittin, a cytolytic peptide that perturbs the lipid bilayer, for effective treatment of stroke and cancer, respectively. Due to their robust properties, simple design, and economic costs, APNPs have great potential to serve as a versatile platform for controlled delivery of therapeutic peptides.

Relating Silica Scaling in Reverse Osmosis to Membrane Surface Properties.

We investigated the relationship between membrane surface properties and silica scaling in reverse osmosis (RO). The effects of membrane hydrophilicity, free energy for heterogeneous nucleation, and surface charge on silica scaling were examined by comparing thin-film composite polyamide membranes grafted with a variety of polymers. Results show that the rate of silica scaling was independent of both membrane hydrophilicity and free energy for heterogeneous nucleation. In contrast, membrane surface charge demonstrated a strong correlation with the extent of silica scaling (R2 > 0.95, p < 0.001). Positively charged membranes significantly facilitated silica scaling, whereas a more negative membrane surface charge led to reduced scaling. This observation suggests that deposition of negatively charged silica species on the membrane surface plays a critical role in silica scale formation. Our findings provide fundamental insights into the mechanisms governing silica scaling in reverse osmosis and highlight the potential of membrane surface modification as a strategy to reduce silica scaling.

Thermodiffusion of polycyclic aromatic hydrocarbons in binary mixtures.

Thermodiffusion in liquid mixtures may explain some counter-intuitive but naturally occurring phenomena such as hydrocarbon reservoirs with heavier component(s) stratified on top of lighter ones. However, beyond benchmark systems, systematic measurements of thermodiffusion in binary organic mixtures are lacking. We use an optical beam deflection apparatus to simultaneously probe Fickian and thermal diffusion in binary solution mixtures of polycyclic aromatic hydrocarbons dissolved in alkanes, and measure both Fickian diffusion D and the Soret coefficient ST, and then obtain the thermodiffusion coefficient DT. In a series of nine binary mixtures, we vary both the size of the aromatic compound from two to four rings, as well as the length of the alkane chain from 6 to 16 carbons. To probe the effect of increasing ring size, we include a 6-ringed aromatic compound, coronene, and toluene as a solvent, due to the insolubility of coronene in alkanes. Our results suggest that Fickian diffusion increases with the inverse of solvent viscosity and also with decreasing molecular weight of the solute. While both of these trends match our intuition, the behavior of ST and DT is more complicated. We find that ST and DT increase with the solute molecular weight when the solvent is held fixed and that the impact of solute ring size is higher in shorter chain alkane solvents.

New Ir Bis-Carbonyl Precursor for Water Oxidation Catalysis.

This paper introduces Ir(I)(CO)2(pyalc) (pyalc = (2-pyridyl)-2-propanoate) as an atom-efficient precursor for Ir-based homogeneous oxidation catalysis. This compound was chosen to simplify analysis of the water oxidation catalyst species formed by the previously reported Cp*Ir(III)(pyalc)OH water oxidation precatalyst. Here, we present a comparative study on the chemical and catalytic properties of these two precursors. Previous studies show that oxidative activation of Cp*Ir-based precursors with NaIO4 results in formation of a blue Ir(IV) species. This activation is concomitant with the loss of the placeholder Cp* ligand which oxidatively degrades to form acetic acid, iodate, and other obligatory byproducts. The activation process requires substantial amounts of primary oxidant, and the degradation products complicate analysis of the resulting Ir(IV) species. The species formed from oxidation of the Ir(CO)2(pyalc) precursor, on the other hand, lacks these degradation products (the CO ligands are easily lost upon oxidation) which allows for more detailed examination of the resulting Ir(pyalc) active species both catalytically and spectroscopically, although complete structural analysis is still elusive. Once Ir(CO)2(pyalc) is activated, the system requires acetic acid or acetate to prevent the formation of nanoparticles. Investigation of the activated bis-carbonyl complex also suggests several Ir(pyalc) isomers may exist in solution. By (1)H NMR, activated Ir(CO)2(pyalc) has fewer isomers than activated Cp*Ir complexes, allowing for advanced characterization. Future research in this direction is expected to contribute to a better structural understanding of the active species. A diol crystallization agent was needed for the structure determination of 3.

Rheology of cellulose nanofibrils in the presence of surfactants.

Cellulose nanofibrils (CNFs) present unique opportunities for rheology modification in complex fluids. Here we systematically consider the effect of ionic and non-ionic surfactants on the rheology of dilute CNF suspensions. Neat suspensions are transparent yield-stress fluids which display strong shear thinning and power-law dependence of modulus on concentration, G' ∼ c(2.1). Surfactant addition below a critical mass concentration cc produces an increase in the gel modulus with retention of optical clarity. Larger than critical concentrations induce significant fibril aggregation leading to the loss of suspension stability and optical clarity, and to aggregate sedimentation. The critical concentration was the lowest for a cationic surfactant (DTAB), cc ≈ 0.08%, while suspension stability was retained for non-ionic surfactants (Pluronic F68, TX100) at concentrations up to 8%. The anionic surfactant SDS led to a loss of stability at cc ≈ 1.6% whereas suspension stability was not compromised by anionic SLES up to 8%. Dynamic light scattering data are consistent with a scenario in which gel formation is driven by micelle-nanofibril bridging mediated by associative interactions of ethoxylated surfactant headgroups with the cellulose fibrils. This may explain the strong difference between the properties of SDS and SLES-modified suspensions. These results have implications for the use of CNFs as a rheology modifier in surfactant-containing systems.

Role of Reverse Divalent Cation Diffusion in Forward Osmosis Biofouling.

We investigated the role of reverse divalent cation diffusion in forward osmosis (FO) biofouling. FO biofouling by Pseudomonas aeruginosa was simulated using pristine and chlorine-treated thin-film composite polyamide membranes with either MgCl2 or CaCl2 draw solution. We related FO biofouling behavior-water flux decline, biofilm architecture, and biofilm composition-to reverse cation diffusion. Experimental results demonstrated that reverse calcium diffusion led to significantly more severe water flux decline in comparison with reverse magnesium permeation. Unlike magnesium, reverse calcium permeation dramatically altered the biofilm architecture and composition, where extracellular polymeric substances (EPS) formed a thicker, denser, and more stable biofilm. We propose that FO biofouling was enhanced by complexation of calcium ions to bacterial EPS. This hypothesis was confirmed by dynamic and static light scattering measurements using extracted bacterial EPS with the addition of either MgCl2 or CaCl2 solution. We observed a dramatic increase in the hydrodynamic radius of bacterial EPS with the addition of CaCl2, but no change was observed after addition of MgCl2. Static light scattering revealed that the radius of gyration of bacterial EPS with addition of CaCl2 was 20 times larger than that with the addition of MgCl2. These observations were further confirmed by transmission electron microscopy imaging, where bacterial EPS in the presence of calcium ions was globular, while that with magnesium ions was rod-shaped.

Ultrathin Nanotube/Nanowire Electrodes by Spin-Spray Layer-by-Layer Assembly: A Concept for Transparent Energy Storage.

Fully integrated transparent devices require versatile architectures for energy storage, yet typical battery electrodes are thick (20-100 µm) and composed of optically absorbent materials. Reducing the length scale of active materials, assembling them with a controllable method and minimizing electrode thickness should bring transparent batteries closer to reality. In this work, the rapid and controllable spin-spray layer-by-layer (SSLbL) method is used to generate high quality networks of 1D nanomaterials: single-walled carbon nanotubes (SWNT) and vanadium pentoxide (V2O5) nanowires for anode and cathode electrodes, respectively. These ultrathin films, deposited with ∼2 nm/bilayer precision are transparent when deposited on a transparent substrate (>87% transmittance) and electrochemically active in Li-ion cells. SSLbL-assembled ultrathin SWNT anodes and V2O5 cathodes exhibit reversible lithiation capacities of 23 and 7 µAh/cm(2), respectively at a current density of 5 µA/cm(2). When these electrodes are combined in a full cell, they retain ∼5 µAh/cm(2) capacity over 100 cycles, equivalent to the prelithiation capacity of the limiting V2O5 cathode. The SSLbL technique employed here to generate functional thin films is uniquely suited to the generation of transparent electrodes and offers a compelling path to realize the potential of fully integrated transparent devices.