Characterization of shapes and volumes of droplets generated in PDMS T-junctions to study nucleation

Santos, Elena C. dos; Ladosz, Agnieszka; Maggioni, Giovanni Maria; Rohr, Philipp Rudolf von; Mazzotti, Marco

doi:10.1016/j.cherd.2018.09.001

Cited by 12 publications

(8 citation statements)

References 22 publications

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“…This procedure applied to the total number of droplets yields a droplet volume distribution, ϕ( v ), here described by the gamma distribution, , characterized by mean value μ v , variance σ v 2 , and coefficient of variation ψ = σ v /μ v . For the sake of clarity, in Figure B we plot droplet volumes recorded for 30 min.…”

Section: Methodsmentioning

confidence: 99%

“…In the context of microfluidic studies of nucleation, this analysis points at the importance of measuring and reporting the droplet volume distribution in detail and in controlling it tightly, so as to minimize its effect on the propagation of experimental uncertainties. It is worth noting that, in our previous study on droplet volume distributions, 9 we had concluded that even a 15% value of the coefficient of variation of the volume distribution would be acceptable for an accurate estimate of the nucleation rate through experiments such as those carried out in this study. That consideration is in principle valid if one considers that the mean value of the success probability is not affected by the coefficient of variation of the volume distribution strongly.…”

Section: Methodsmentioning

confidence: 99%

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Statistical Analysis and Nucleation Parameter Estimation from Nucleation Experiments in Flowing Microdroplets

Santos

Maggioni

Mazzotti

2019

Crystal Growth & Design

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We have studied the primary nucleation of adipic acid from aqueous solutions in thousands of microdroplets generated in a fully automated microfluidic setup. By varying supersaturation in solution and residence time, we were able to estimate nucleation rates and growth times, while accounting for the stochastic nature of nucleation, the variability in microdroplet volumes (which is kept below 2%, thanks to a carefully designed experimental protocol), and the uncertainty in the automated image analysis procedure. Through a thorough statistical analysis we have obtained exact expressions for the expected values and the variances of all the random variables involved, all the way to the nucleation rate and the growth time associated with each supersaturation level explored and to the model parameters appearing in the corresponding constitutive equations. We have analyzed what controls the overall uncertainty in the estimation of the physical quantities above. We have shown that the distribution of droplet volumes at the level observed here is not limiting, whereas the detection technique and the image analysis algorithm play a critical role, together with the fact that the supersaturation levels and residence times that can be reasonably explored are limited. The tools and methods presented and made available to the scientific community will help in making microfluidics-based studies of nucleation more effective.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Statistical Analysis and Nucleation Parameter Estimation from Nucleation Experiments in Flowing Microdroplets

Santos

Maggioni

Mazzotti

2019

Crystal Growth & Design

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“…[153] The droplet volume can also be precisely controlled, which is essential to the analysis of nucleation kinetics. [154] Measurement of the evolution of the fraction of droplets that contain crystals over time under constant supersaturation therefore yields the nucleation kinetics, [68] as discussed in Section 5.2.1. Analysis of nucleation kinetics has been carried out for a wide range of systems including proteins, [155,156] soluble organics [156,157] and inorganics, [68,70,85,158] poorly-soluble compounds, [159,160] and the solidification of melts, [161,162] and most systems exhibit complex nucleation kinetics due to multiple pathways.…”

Section: Segmented-flow Microfluidic Systemsmentioning

confidence: 99%

Crystallization in Confinement

2020

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Many crystallization processes of great importance, including frost heave, biomineralization, the synthesis of nanomaterials, and scale formation, occur in small volumes rather than bulk solution. Here, the influence of confinement on crystallization processes is described, drawing together information from fields as diverse as bioinspired mineralization, templating, pharmaceuticals, colloidal crystallization, and geochemistry. Experiments are principally conducted within confining systems that offer well‐defined environments, varying from droplets in microfluidic devices, to cylindrical pores in filtration membranes, to nanoporous glasses and carbon nanotubes. Dramatic effects are observed, including a stabilization of metastable polymorphs, a depression of freezing points, and the formation of crystals with preferred orientations, modified morphologies, and even structures not seen in bulk. Confinement is also shown to influence crystallization processes over length scales ranging from the atomic to hundreds of micrometers, and to originate from a wide range of mechanisms. The development of an enhanced understanding of the influence of confinement on crystal nucleation and growth will not only provide superior insight into crystallization processes in many real‐world environments, but will also enable this phenomenon to be used to control crystallization in applications including nanomaterial synthesis, heavy metal remediation, and the prevention of weathering.

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“…It is interesting that the same general behavior was not only already reported for similar geometries producing double emulsions, [32,53] but also for simple T-junctions operating at much lower capillary numbers. [54,55] This suggests that despite their apparent complexity, at the dripping regime double emulsions follow the same rules of formation as single droplets, as long as the inner droplet is stable inside the envelope of the organic phase. Second, the OA phase flow rate was set to a constant value above the threshold, that is, Q OA = 50 µL min −1 , and the flow rate ratio Q IA /Q PO was varied.…”

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confidence: 99%

Combinatorial Strategy for Studying Biochemical Pathways in Double Emulsion Templated Cell‐Sized Compartments

et al. 2020

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optimize these pathways and thus to guarantee their maximum chance of survival, cells produce enzymes at precise and constant rates. [4] However, because of cellular complexity, determination of optimal enzyme levels is still unclear, in particular because specific enzymatic functions are strongly interconnected with their cascade effects. [5] A smart manner to study the behavior of enzymes, when involved in complex reactions, consists of taking advantage of synthetic micrometer-sized compartments shaped into spherical architectural bodies. [6-8] Though these idealized models favor even partitioning of membrane proteins and simplify diffusion gradients, similarly to cells, they provide the desired membrane selectivity and permeability. [9,10] Single specific functions have been presented by combining enzymes (the catalytic compounds) with synthetic supramolecular assemblies, either intrinsically semipermeable, such as lipid-coated porous silica particles, [11] protein cages, [12] layer-by-layer capsules, [13-15] and polydopamine capsules, [16,17] or rendered permeable by the insertion of biopores/membrane proteins (acting as "gates" for the passage of molecules), as in lipid-based [7,18,19] or polymer-based [8,20-22] giant unilamellar vesicles (GUVs). At present, GUVs formed with amphiphilic block copolymers are particularly appealing because they provide enhanced structural membrane properties compared to lipids, since they possess compartments with higher chemical versatility, controlled permeability, robustness, and stability. [23] Nevertheless, common approaches to form polymer GUVs by self-assembly, as electroformation [24] and film-rehydration, [25] rely on the statistical process of encapsulation of biomolecules with a probability of finding the designed amount of one type of enzyme inside the compartments ranging from 12-57%. In the context of elementary biochemical pathways where at least two enzymes are present, this scenario is even more unsatisfactory, with co-encapsulation of two enzymes inside one compartment as low as 10-22%. [26,27] These shortcomings are worsened by the fact that these probabilities have a large uncertainty induced by specific properties of enzymes (e.g., solubility and stability). To date, scientists have struggled to work with stateof-the-art average values for number/mass of enzymes that are vastly non-representative (limited by a small sample size) Cells rely upon producing enzymes at precise rates and stoichiometry for maximizing functionalities. The reasons for this optimal control are unknown, primarily because of the interconnectivity of the enzymatic cascade effects within multi-step pathways. Here, an elegant strategy for studying such behavior, by controlling segregation/combination of enzymes/ metabolites in synthetic cell-sized compartments, while preserving vital cellular elements is presented. Therefore, compartments shaped into polymer GUVs are developed, producing via high-precision double-emulsion microfluidics that enable: i) tight control over the absolute and...

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Characterization of shapes and volumes of droplets generated in PDMS T-junctions to study nucleation

Cited by 12 publications

References 22 publications

Statistical Analysis and Nucleation Parameter Estimation from Nucleation Experiments in Flowing Microdroplets

Statistical Analysis and Nucleation Parameter Estimation from Nucleation Experiments in Flowing Microdroplets

Crystallization in Confinement

Combinatorial Strategy for Studying Biochemical Pathways in Double Emulsion Templated Cell‐Sized Compartments

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