Multimaterial 3D printing facilitates the rapid production of complex devices with integrated materials of varying properties and functionality. Herein, multimaterial fused deposition modeling (MM-FDM) 3D printing was applied to the fabrication of low-cost passive sampler devices with integrated porous membranes. Using MM-FDM 3D printing, the device body was produced using black polylactic acid, with Poro-Lay Lay-Felt filament used for the printing of the integrated porous membranes (rubber-elastomeric polymer, porous after removal of a water-soluble poly(vinyl alcohol) component). The resulting device consisted of two interlocking circular frames, each containing the integrated membrane, which could be efficiently sealed together without the need for additional O-rings, and prevented loss of enclosed microparticulate sorbent. Scanning electron microscopy (SEM) analysis of the purified composite filament confirmed the porous properties of the material, an average pore size of ∼30 nm. The printed passive samplers with various membrane thicknesses, including 0.5, 1.0, and 1.5 mm, were evaluated for their ability to facilitate the extraction of atrazine as the model solute onto the internal sorbent, under standard conditions. Gas chromatography-mass spectrometry was used to determine the uptake of atrazine by the device from standard water samples and also to evaluate any chemical leaching from the printed materials. The sampler with 0.5 mm thick membrane showed the best performance with 87% depletion and a sampling rate of 0.19 Ld ( n = 3, % RSD = 0.59). The results obtained using these printed sampling devices with integrated membranes were in close agreement to devices fitted with a standard poly(ether sulfone) membrane.
Oil-in-water (‘inverse’) High Internal Phase Emulsions (HIPEs) have been prepared using an amphiphilic macro-RAFT agent with toluene as the internal dispersed phase (∼80 vol%) and an aqueous monomer solution as the continuous phase.
Polymer monoliths were prepared in 150 μm id capillaries by thermally initiated polymerization of PEG diacrylate for rapid hydrophobic interaction chromatography of immunoglobulin G (IgG) subclasses and related variants. Using only one monomer in the polymerization mixture allowed ease of optimization and synthesis of the monolith. The performance of the monolith was demonstrated by baseline resolution of IgG subclasses and variants, including mixtures of the κ variants of IgG1, IgG2, and IgG3 as well as the κ and λ variants associated with IgG1 and IgG2. The effect of eluent concentration and pH on the separation efficiency of studied proteins was also explored, allowing almost baseline resolution to be achieved for mixtures of the κ variants of IgG1, IgG2, IgG3, and IgG4 but also for the κ and λ variants of IgG1 and IgG2. The results showed significant improvement in the separations in terms of the tradeoff between analysis time and resolution, while maintaining a simple methodology, in comparison to previous reports. The synthesized monolith was also used for the separation of isoforms of a therapeutic monoclonal antibody.
The applicability of mass spectrometry imaging (MSI) has exponentially increased with the improvement of sample preparation, instrumentation (spatial resolution) and data analysis. The number of MSI publications listed in PubMed continues to grow with 378 published articles in 2020‐2021. Initially, MSI was just sensitive enough to identify molecular features correlating with distinct tissue regions, similar to the resolution achieved by visual inspection after standard immunohistochemical staining. Although the spatial resolution was limited compared with other imaging modalities, the molecular intensity mapping added a new exciting capability. Over the past decade, significant improvements in every step of the workflow and most importantly in instrumentation were made, which now enables the molecular analysis at a cellular and even subcellular level. Here, we summarize the latest developments in MSI, with a focus on the latest approaches for tissue‐based imaging described in 2020.
The influence of the addition of various non-ionic surfactants to poly(ethylene glycol) diacrylate-based monolith formulations was studied. Eight non-ionic surfactants having different chemistries were chosen for this study. These surfactants were Brij L4, Span 80, IGEPAL Tergitol 15S9,2,4,7, Tween 40,, and Tetronic 701. The chemical structures of these surfactants have a variety of functional groups and cover a wide range of molecular weights (360−3600 g/mol), viscosities (60−1500 cP), and hydrophilic−lipophilic balances (1.0−17.6). The formed polymers were characterized by scanning electron microscopy, surface area measurement by the Brunauer−Emmet− Teller method, elemental analysis, and Fourier transform infrared. Four formulations, involving the use of surfactants, resulted in permeable materials when prepared in 150 μm ID silica capillaries. The chromatographic performance of the resulting columns in reversed-phase mode was evaluated and compared using a mixture of alkyl benzenes as test analytes. The highest efficiency and methylene selectivity were observed when Tween 40 was included in the formulation, using decane/decanol/dodecanol as coporogens. This porogenic mixture was successfully used for preparation of monolithic columns from a selection of methacrylate-and styrene-based monomers, including butylmethacrylate, hydroxyethymethacrylate, laurylmethacrylate, glycidyl methacrylate, bisphenol diacrylate, benzylmethacrylate, and N,N-dimethylacrylamide, as well as for divinylbenzene. These results show the applicability of this porogenic mixture for a variety of monolithic formulations, providing an approach for developing a universal porogen system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.