Solvents, Buffers, and Additives Used in the Mobile Phase

Moldoveanu, Serban C.; David, Víctor

doi:10.1016/b978-0-12-803684-6.00013-5

Cited by 8 publications

(6 citation statements)

References 104 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The PD of particles in isopropanol likely decreased due to its diffusion coefficient and viscosity, which would result in an increase in OR. [40] Isopropanol 0.79 [37] 2.37 [37] 3.9 [38] 0.25 [38] 0.92 [39] 1 Expected value of −0.34 [38].…”

Section: Effect Of Solvent Type On Zein Np Size and Pdmentioning

confidence: 99%

Using a Microfluidics System to Reproducibly Synthesize Protein Nanoparticles: Factors Contributing to Size, Homogeneity, and Stability

et al. 2019

View full text Add to dashboard Cite

The synthesis of Zein nanoparticles (NPs) using conventional methods, such as emulsion solvent diffusion and emulsion solvent evaporation, is often unreliable in replicating particle size and polydispersity between batch-to-batch syntheses. We have systematically examined the parameters for reproducibly synthesizing Zein NPs using a Y-junction microfluidics chip with staggered herringbone micromixers. Our results indicate that the total flow rate of the fluidics system, relative flow rate of the aqueous and organic phase, concentration of the base material and solvent, and properties of the solvent influence the polydispersity and size of the NPs. Trends such as increasing the total flow rate and relative flow rate lead to a decrease in Zein NP size, while increasing the ethanol and Zein concentration lead to an increase in Zein NP size. The solvent property that was found to impact the size of the Zein NPs formed the most was their hydropathy. Solvents that had a hydropathy index most similar to that of Zein formed the smallest Zein NPs. Synthesis consistency was confirmed within and between sample batches. Stabilizing agents, such as sodium caseinate, Tween 80, and Pluronic F-68, were incorporated using the microfluidics system, necessary for in vitro and in vivo use, into Zein-based NPs.

show abstract

Section: Effect Of Solvent Type On Zein Np Size and Pdmentioning

confidence: 99%

Using a Microfluidics System to Reproducibly Synthesize Protein Nanoparticles: Factors Contributing to Size, Homogeneity, and Stability

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The liquid junction between the RE, its filling solution, and the solution under test was identified as being the main contributor to inter-electrode variability. This conclusion has been drawn for both low ionic strength (poor buffering capacity) aqueous solutions [ 46 ] and buffered alcohol–water mixtures [ 29 ]. The signal from the RE component of the combination pH electrodes employed here (electrodes B through F) is not used in the current investigation.…”

Section: Discussionmentioning

confidence: 90%

“…Ethanol is selected due to its use as bioethanol in fuel applications. Although methanol and acetonitrile are selected as they are the two solvents used most extensively in liquid chromatography separation [ 29 ]. A prior European metrology joint research project (BIOREMA) organized a comparison on a bioethanol reference material, including the assessment of pHe according to methods specified in various standards [ 30 ], showed poor comparability of results.…”

Section: Introductionmentioning

confidence: 99%

“…Although individual s pH results have been published for methanol and acetonitrile [ 4 , 31 , 32 ], the evaluation of the reliability of these results over a wider composition range are missing from the literature. Although applications of methanol and acetonitrile to liquid chromatography are combined with buffering agents [ 29 ], the use of ethanol in biofuels is un-buffered [ 33 ]. Here, measurements with un-buffered solutions, without the addition of other spectator ions, are examined.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Unified pH Measurements of Ethanol, Methanol, and Acetonitrile, and Their Mixtures with Water

Deleebeeck

Snedden

Dániel

et al. 2021

Sensors

View full text Add to dashboard Cite

Measurement of pH in aqueous-organic mixtures with different compositions is of high importance in science and technology, but it is, at the same time, challenging both from a conceptual and practical standpoint. A big part of the difficulty comes from the fundamental incomparability of conventional pH values between solvents (spH, solvent-specific scales). The recent introduction of the unified pH (pHabs) concept opens up the possibility of measuring pH, expressed as pHabsH2O, in a way that is comparable between solvent, and, thereby, removing the conceptual problem. However, practical issues remain. This work presents the experience of the authors with measuring pHabsH2O values in mixtures of methanol, ethanol, and acetonitrile, with water, but without the presence of buffers or other additives. The aim was to assigned pHabsH2O values to solvent–water mixtures using differential potentiometry and the ‘pHabs-ladder’ method. Measurements were made of the potential difference between glass electrodes immersed in different solutions, separated by an ionic liquid salt bridge. Data were acquired for a series of solutions of varying solvent content. This work includes experiences related to: a selection of commercial electrodes, purity of starting material, and comparability between laboratories. Ranges of pHabsH2O values for selected compositions of solvent–water mixtures are presented.

show abstract

“…For the determination of tunneling resistance, the graphene height of rectangular potential barrier is set to 4.6 eV [ 42 ], the PPy dielectric constant is

[ 43 ], and the permittivity of free space is

[ 44 ]. Figure 4 shows the calculated results for the tunneling resistance of graphene–PPy–graphene.…”

Section: Resultsmentioning

confidence: 99%

Computational Study of Graphene–Polypyrrole Composite Electrical Conductivity

et al. 2021

View full text Add to dashboard Cite

In this study, the electrical properties of graphene–polypyrrole (graphene-PPy) nanocomposites were thoroughly investigated. A numerical model, based on the Simmons and McCullough equations, in conjunction with the Monte Carlo simulation approach, was developed and used to analyze the effects of the thickness of the PPy, aspect ratio diameter of graphene nanorods, and graphene intrinsic conductivity on the transport of electrons in graphene–PPy–graphene regions. The tunneling resistance is a critical factor determining the transport of electrons in composite devices. The junction capacitance of the composite was predicted. A composite with a large insulation thickness led to a poor electrochemical electrode. The dependence of the electrical conductivity of the composite on the volume fraction of the filler was studied. The results of the developed model are consistent with the percolation theory and measurement results reported in literature. The formulations presented in this study can be used for optimization, prediction, and design of polymer composite electrical properties.

show abstract

Solvents, Buffers, and Additives Used in the Mobile Phase

Cited by 8 publications

References 104 publications

Using a Microfluidics System to Reproducibly Synthesize Protein Nanoparticles: Factors Contributing to Size, Homogeneity, and Stability

Using a Microfluidics System to Reproducibly Synthesize Protein Nanoparticles: Factors Contributing to Size, Homogeneity, and Stability

Unified pH Measurements of Ethanol, Methanol, and Acetonitrile, and Their Mixtures with Water

Computational Study of Graphene–Polypyrrole Composite Electrical Conductivity

Contact Info

Product

Resources

About