Advanced analysis of polymer emulsions: Particle size and particle size distribution by field-flow fractionation and dynamic light scattering

Poly(Vinyl Acetate) Paints: A Literature Review of Material Properties, Ageing Characteristics, and Conservation Challenges

Since their development in the 1950s, poly(vinyl acetate) [PVAc] paints (also known as vinyl) have been used by many artists, most notably in countries such as Spain, Portugal, and the United Kingdom; they are also used globally as a common binder for house paints. However, only a relatively limited number of heritage scientific studies have focused on vinyl paints. Consequently, many critical aspects of this material, such as the degradation processes, variations in paint formulations, and responses to conservation treatments, remain largely understudied. This article aims to summarise the available relevant information on poly(vinyl acetate) paints from both the scientific and the conservation practice perspectives. The article provides a brief overview of the development of poly(vinyl acetate) paints as artist-grade and household products and the known differences in their formulations. It also focuses on poly(vinyl acetate) ageing behaviour, the physicochemical properties, the recent scientific research on poly(vinyl acetate) material characterisation and degradation, and the main conservation issues regarding these paints, such as those relating to cleaning treatments.

Novel zone elution mode in coiled tube field-flow fractionation for online separation and characterization of environmental submicron particles

Coiled tube field-flow fractionation (CTFFF) is currently applied to environmental and material studies. In the present work, a novel zone elution mode in CTFFF has been proposed and developed. Zone elution mode is based on the separation of particles by stepwise decreasing the flow rate of the carrier fluid and their subsequent elution at a constant flow rate. The fractionation parameters were optimized using a mixture of standard silica submicron particles (150, 390, and 900 nm). Taking samples of volcanic ash as examples, it has been demonstrated that zone elution mode can be successfully used for the fractionation of environmental nano- and submicron particles. For the first time, CTFFF was coupled online with a dynamic light scattering detector for the size characterization of eluted particles. Zone elution in CTFFF can serve for the further development of hyphenated techniques enabling efficient fractionation and size/elemental characterization of environmental particles in nano- and submicrometric size ranges.

Detection, Identification and Size Distribution of Silver Nanoparticles (AgNPs) in Milk and Migration Study for Breast Milk Storage Bags

The engineered silver nanoparticles (AgNPs) have been widely used in various food contact materials (FCMs) based on their antibacterial properties. This widespread use of nanosilver has, however, increased the risk of exposure of AgNPs to human due to their migration from FCMs causing a potential hazard present in foods. Therefore, it is important to establish a reliable and practical method for the detection of AgNPs in food matrices to support risk assessment on AgNPs exposure. Taking the examples of milk and AgNPs-containing breast milk storage bags, this study established an approach for size characterization and quantification of AgNPs in milk and evaluated the relevant silver migration, based on enzymatic digestion and the analysis by asymmetric flow field–flow fractionation (AF4) hyphenated with inductively coupled plasma mass spectrometry (ICP-MS) and single particle inductively coupled plasma mass spectrometry (SP-ICP-MS). No migration of AgNPs was found from breast milk storage bags under various simulated storage conditions as well as extreme scenarios. The suitability and reliability of this method were also validated by the determination of multiple parameters, including accuracy, repeatability, limit of detection (LOD), limit of quantification (LOQ), and recovery, for AF4-ICP-MS and SP-ICP-MS, respectively, with good and overall acceptable evaluation results obtained for all. The established and validated approach was demonstrated to be suitable for the characterization and quantitation of AgNPs in milk as well as the analysis of their migration from breast milk storage bags.

Field-flow fractionation for nanoparticle characterization

This review presents field-flow fractionation: The elements of theory enable the link between the retention and the characteristics of the nanometer-sized analytes to be highlighted. In particular, the nature of force and its way of being applied are discussed. Four types of forces which determine four types of techniques were considered: hydrodynamic, sedimentation, thermal, and electrical; this is to show the importance of the choice of technique in relation to the characterization objectives. Then the separation performance is presented and compared with other separation techniques: field-flow fractionation has the greatest intrinsic separation capability. The characterization strategies are presented and discussed; on the one hand with respect to the characteristics needed for the description of nanoparticles; on the other hand in connection with the choice of the nature of the force, and also of the detectors used, online or offline. The discussion is based on a selection of published study examples. Finally, current needs and challenges are addressed, and as response, trends and possible characterization solutions.

Asymmetric flow field-flow fractionation as a multifunctional technique for the characterization of polymeric nanocarriers

The importance of polymeric nanocarriers in the field of drug delivery is ever-increasing, and the accurate characterization of their properties is paramount to understand and predict their behavior. Asymmetric flow field-flow fractionation (AF4) is a fractionation technique that has gained considerable attention for its gentle separation conditions, broad working range, and versatility. AF4 can be hyphenated to a plurality of concentration and size detectors, thus permitting the analysis of the multifunctionality of nanomaterials. Despite this potential, the practical information that can be retrieved by AF4 and its possible applications are still rather unfamiliar to the pharmaceutical scientist. This review was conceived as a primer that clearly states the "do's and don'ts" about AF4 applied to the characterization of polymeric nanocarriers. Aside from size characterization, AF4 can be beneficial during formulation optimization, for drug loading and drug release determination and for the study of interactions among biomaterials. It will focus mainly on the advances made in the last 5 years, as well as indicating the problematics on the consensus, which have not been reached yet. Methodological recommendations for several case studies will be also included.

Separation and size characterization of highly polydisperse titanium dioxide nanoparticles (E171) in powdered beverages by using Asymmetric Flow Field-Flow Fractionation hyphenated with Multi-Angle Light Scattering and Inductively Coupled Plasma Mass Spectrometry

The application of titanium dioxide as E171 food additive has become an issue of debate due to numerous reports that titanium dioxide nanoparticles (TiO₂ NPs) inside the products may pose risks to human health. However, there is still a lack of an official standardized methodology for the detection and size characterization of TiO₂ particles in foods containing E171. In this study, a method was presented for size characterization of TiO₂ particles with various independent verifications in coffee creamer and instant drink powders, using Asymmetric Flow Field-Flow Fractionation hyphenated with Multi-Angle Light Scattering and Inductively Coupled Plasma Mass Spectrometry (AF4-MALS-ICP-MS). TiO₂ particles from these products were well extracted, followed by their optimized AF4 separation using anionic surfactant Sodium Dodecyl Sulfate (SDS) (0.05%, pH 9) and mixed surfactant NovaChem (0.2%), respectively. Size determination of TiO₂ NPs was conducted based on AF4 calibration with polystyrene nanospheres and verification with TiO₂ NPs standard suspension of 100 nm under two different AF4 conditions. The TiO₂ particle sizes detected ranged from 24.4 - 544.3 nm for coffee creamer and 27.7 - 574.3 nm for instant drink powders, with the TiO₂ NPs detection recoveries of 75% and 92%, respectively. Hydrodynamic diameters from AF4 size calibration could be independently validated by the gyration diameters from online MALS measurement. The established approach was demonstrated to be reliable and pragmatic for size profiling of highly polydisperse TiO₂ particles and thus useful for monitoring E171 in similar foodstuffs.

Preparation and anti-leakage properties of hydroxyethyl cellulose-g-poly (butyl acrylate-co-vinyl acetate) emulsion

A hydroxyethyl cellulose-g-poly (butyl acrylate-co-vinyl acetate)(HEC-g-P (BA-co-VAc)) emulsion was synthesized by free radical emulsion polymerization method from hydroxyethyl cellulose (HEC), butyl acrylate (BA) and vinyl acetate (VAc) in the presence of emulsifier sodium dodecyl benzene sulfonate (SDBS). The structure, thermal stability and morphology of the emulsion were characterized by Fourier-transform infrared (FTIR), thermogravimetric analysis (TGA), transmission electron microscope (TEM) and other analytical techniques. The results proved that BA and VAc monomers had grafted with HEC. Its thermal stability was also significantly improved compared to HEC. Moreover, the prepared emulsion was evaluated to study the performance of preventing water leakage in soil. Compared with the published anti-leakage materials prepared by directly doping hydroxyethyl cellulose, the emulsion interacted with attapulgite to form a dense consolidation layer, which had better anti-leakage performance and water retention. Therefore, the material was more favorable for popularization and application in arid and semi-arid areas.

Synthesis and Characterization of a Core-Shell Copolymer with Different Glass Transition Temperatures

The aim of this study is to synthesize an organic core-shell co-polymer with a different glass transition temperature (Tg) between the core and the shell that can be used for several applications such as the selective debonding of coatings or the release of encapsulated materials. The co-polymer was synthesized using free radical polymerization and was characterized with respect to its morphology, composition and thermal behavior. The obtained results confirmed the successful synthesis of the co-polymer copolymer poly(methyl methacrylate)@poly(methacrylic acid-co-ethylene glycol dimethacrylate), PMMA@P(MAA-co-EGDMA), which can be used along with water-based solvents. Furthermore, the Tg of the polymer’s core PMMA was 104 °C, while the Tg of the shell P(MAA-co-EGDMA) was 228 °C, making it appropriate for a wide variety of applications. It is worth mentioning that by following this specific experimental procedure, methacrylic acid was copolymerized in water, as the shell of the copolymer, without forming a gel-like structure (hydrogel), as happens when a monomer is polymerized in aqueous media, such as in the case of super-absorbent polymers. Moreover, the addition and subsequent polymerization of the monomer methyl methacrylate (MAA) into the mixture of the already polymerized PMMA resulted in a material that was uniform in size, without any agglomerations or sediments.

Machine-learning-based computationally efficient particle size distribution retrieval from bulk optical properties

Retrieval of particle size distribution from bulk optical properties based on evolutionary algorithms is usually computationally expensive. In this paper, we report an efficient numerical approach to solving the inverse scattering problem by accelerating the calculation of bulk optical properties based on machine learning. With the assumption of spherical particles, the forward scattering by particles is first solved by Mie scattering theory and then approximated by machine learning. The particle swarm optimization algorithm is finally employed to optimize the particle size distribution parameters by minimizing the deviation between the target and simulated bulk optical properties. The accuracies of machine learning and particle swarm optimization are separately investigated. Meanwhile, both monomodal and bimodal size distributions are tested, considering the influences of random noise. Results show that machine learning is capable of accurately predicting the scattering efficiency for a specific size distribution in approximately 0.5 µs on a standalone computer. Therefore, the proposed method has the potential to serve as a powerful tool in real-time particle size measurement due to its advantages of simplicity and high efficiency.

An effective approach for size characterization and mass quantification of silica nanoparticles in coffee creamer by AF4-ICP-MS

Silicon dioxide (SiO₂) has been used as a food additive (E551) for decades. However, some safety concerns have been raised recently due to the detection of silica nanoparticles (SiO₂ NPs) in a variety of foodstuffs and their unknown long-term health risk to humans. In order for risk assessment to be conducted, it is essential to establish a reliable, valid, and pragmatic method for analysis of SiO₂ NPs in foods for estimation of exposure. This paper presents an effective approach for both size characterization and mass quantification of SiO₂ NPs in commercial high-fat coffee creamer using asymmetric flow field-flow fractionation (AF4) coupled to inductively coupled plasma mass spectrometry (ICP-MS). SiO₂ NPs from coffee creamer were well extracted after cleanup with hexane in a two-phase (hexane vs. water) aqueous environment. Size determination of SiO₂ NPs was performed by on-line AF4-ICP-MS based on calibration with monodispersed standards. The dominant primary size of SiO₂ NPs in the studied sample was 36.5 nm. The mass percentages of SiO₂ NPs (vs. total SiO₂) were 18.6% for the dominant primary nano-silica particles by prechannel calibration and 35.7% for total SiO₂ NPs (≤ 100 nm) by postchannel calibration, with recoveries of 89-96% for the former and 75% for the latter. The established approach was demonstrated to be efficient and practical for routine analysis of polydispersed SiO₂ NPs with wide nano-size distribution in coffee creamer. This method may be extended to monitor the presence of SiO₂ NPs in other similar complex food matrices. Graphical abstract.

Early Development Challenges for Drug Products Containing Nanomaterials

The vast majority of drug product candidates in early development fail to progress to clinics. This is true for products containing nanomaterials just as for other types of pharmaceuticals. Early development pathways should therefore place high priority on experiments that help candidates fail faster and less expensively. Nanomedicines fail for many reasons, but some are more avoidable than others. Some of the points of failure are not considerations in the development of small molecules or biopharmaceuticals, and so may be unexpected, even to those with previous experience bringing drug products to the clinic. This article reviews experiments that have proven useful in providing "go/no-go" decision-making data for nanomedicines in early preclinical development. Of course, the specifics depend on the particulars of the drug product and the nanomaterial type, and not every product shares the same development pathway or the same potential points of failure. Here, we focus on challenges that differ from those in the development of traditional small molecule therapeutics, and on experiments that reveal deficiencies that can only be corrected by essentially starting over-altering the nanomedicine to an extent that all previous characterization and proof-of-concept testing must be repeated. Conducting these experiments early in the development process can save significant resources and time and allow developers to focus on derisked candidates with a greater likelihood of ultimate success.