Bulk Free Radical Terpolymerization of Butyl Acrylate, 2-Methylene-1,3-Dioxepane and Vinyl Acetate: Terpolymer Reactivity Ratio Estimation.

This investigation introduces the first estimation of ternary reactivity ratios for a butyl acrylate (BA), 2-methylene-1,3-dioxepane (MDO), and vinyl acetate (VAc) system at 50 °C, with an aim to develop biodegradable pressure-sensitive adhesives (PSAs). In this study, we applied the error-in-variables model (EVM) to estimate reactivity ratios. The ternary reactivity ratios were found to be r12 = 0.417, r21 = 0.071, r13 = 4.459, r31 = 0.198, r23 = 0.260, and r32 = 55.339 (BA/MDO/VAc 1/2/3), contrasting with their binary counterparts, which are significantly different, indicating the critical need for ternary system analysis to accurately model multicomponent polymerization systems. Through the application of a recast Alfrey-Goldfinger model, this investigation predicts the terpolymer's instantaneous and cumulative compositions at various conversion levels, based on the ternary reactivity ratios. These predictions not only provide crucial insights into the incorporation of MDO across different initial feed compositions but also offer estimates of the final terpolymer compositions and distributions, underscoring their potential in designing compostable or degradable polymers.

Detection of Volatile Organic Compounds by Using MEMS Sensors.

We report on the deployment of MEMS static bifurcation (DC) sensors for the detection of volatile organic compounds (VOCs): hydrogen sulfide and formaldehyde. We demonstrate a sensor that can detect as low as a few ppm of hydrogen sulfide. We also demonstrate a sensor array that can selectively detect formaldehyde in the presence of benzene, a closely related interferent. Toward that end, we investigate the sensitivity and selectivity of two detector polymers-polyaniline (PANI) and poly (2,5-dimethyl aniline) (P25DMA)-to both gases. A semiautomatic method is developed to functionalize individual sensors and sensor arrays with the detector polymers. We found that the sensor array can selectively sense 1 ppm of formaldehyde in the presence of benzene.

Performance Evaluation of Nonacosan-10-ol-Based Polyethylene Packaging Material Using Molecular Dynamics Simulations.

Packaging material has a significant role in maintaining or altering the shelf life of different products. Polymer materials are extensively used as packaging materials for different perishable and non-perishable products both during transportation and storage. This article aims at developing a new polymer composite which can be used as packaging material. This new composite addresses the challenge of controlling oxygen diffusion rates during the storage of perishable goods such as vegetables, meat and produce, etc. The proposed new composite primarily consists of nonacosan-10-ol and polyethylene. Molecular dynamics simulations (MDS) are performed by mixing 5.2%, 17.1%, 29.2%, 40.8% and 45.2% (wt/wt) of nonacosan-10-ol to amorphous polyethylene. Mechanical properties such as Young's modulus/glass transition temperature, and gas transport properties such as diffusion coefficient and diffusion volume are estimated from the MDS and diffusion related simulations consisting of different oxygen concentrations in polyethylene-alone system and polyethylene- nonacosan-10-ol blends. The impact of adding different weight percent of nonacosan-10-ol to polyethylene is quantitatively assessed and optimal composition of the proposed additive is suggested corresponding to minimal oxygen diffusion rate, high elastic modulus and good thermal stability.

Intelligent Machine Learning: Tailor-Making Macromolecules.

Nowadays, polymer reaction engineers seek robust and effective tools to synthesize complex macromolecules with well-defined and desirable microstructural and architectural characteristics. Over the past few decades, several promising approaches, such as controlled living (co)polymerization systems and chain-shuttling reactions have been proposed and widely applied to synthesize rather complex macromolecules with controlled monomer sequences. Despite the unique potential of the newly developed techniques, tailor-making the microstructure of macromolecules by suggesting the most appropriate polymerization recipe still remains a very challenging task. In the current work, two versatile and powerful tools capable of effectively addressing the aforementioned questions have been proposed and successfully put into practice. The two tools are established through the amalgamation of the Kinetic Monte Carlo simulation approach and machine learning techniques. The former, an intelligent modeling tool, is able to model and visualize the intricate inter-relationships of polymerization recipes/conditions (as input variables) and microstructural features of the produced macromolecules (as responses). The latter is capable of precisely predicting optimal copolymerization conditions to simultaneously satisfy all predefined microstructural features. The effectiveness of the proposed intelligent modeling and optimization techniques for solving this extremely important 'inverse' engineering problem was successfully examined by investigating the possibility of tailor-making the microstructure of Olefin Block Copolymers via chain-shuttling coordination polymerization.

Modelling permeation passive sampling: intra-particle resistance to mass transfer and comprehensive sensitivity analysis.

A mathematical model developed previously to describe the sampling process in permeation passive samplers with non-porous adsorbents and evaluated using the Waterloo Membrane Sampler (WMS) is here extended to include adsorbents with porous particles. This work was motivated by the need to expand the model applicability to include the various types of adsorbents used in the WMS, and to develop a deep understanding of the model sensitivity towards required parameters. The effects of intraparticle porosity on the effective diffusivity of the analyte in a bed of porous particles and on the mass transfer coefficient for analyte transport from the interparticle void phase to the porous solid phase are both evaluated. Experimental validation of the applicability of the model on adsorbents with microporous particles was carried out using the WMS containing Anasorb 747, a carbon-based adsorbent with highly porous particles. Good agreement between the experimental and model results was found. A comprehensive sensitivity analysis was also conducted to identify the parameters with the greatest influence on the results of the calculated uptake rate. This analysis included two types of adsorbents with different sorption strengths. The results showed that the uptake rate sensitivity is limited to parameters related to mass transfer in the membrane for strong adsorbents. On the other hand, sensitivity to parameters related to mass transfer in the sorbent bed becomes more significant as the strength of the adsorbent decreases; however, this effect can be reduced by increasing the membrane thickness. Influential parameters in the sorbent bed are also affected by the temperature. Nevertheless, the contribution of this change to the total effect of temperature change on the uptake rate is expected to be negligible within the small range of temperature variations usually encountered during a single environmental sampling event, especially in soil-gas sampling which is the most widely used application of the WMS.

Role of contact electrification and electrostatic interactions in gecko adhesion.

Geckos, which are capable of walking on walls and hanging from ceilings with the help of micro-/nano-scale hierarchical fibrils (setae) on their toe pads, have become the main prototype in the design and fabrication of fibrillar dry adhesives. As the unique fibrillar feature of the toe pads of geckos allows them to develop an intimate contact with the substrate the animal is walking on or clinging to, it is expected that the toe setae exchange significant numbers of electric charges with the contacted substrate via the contact electrification (CE) phenomenon. Even so, the possibility of the occurrence of CE and the contribution of the resulting electrostatic interactions to the dry adhesion of geckos have been overlooked for several decades. In this study, by measuring the magnitude of the electric charges, together with the adhesion forces, that gecko foot pads develop in contact with different materials, we have clarified for the first time that CE does contribute effectively to gecko adhesion. More importantly, we have demonstrated that it is the CE-driven electrostatic interactions which dictate the strength of gecko adhesion, and not the van der Waals or capillary forces which are conventionally considered as the main source of gecko adhesion.

Instabilities of Teflon AF thin films in alumina nanochannels and adhesion of bi-level Teflon AF nanopillars.

In this paper, a novel replica-molding technique for fabrication of bi-level Teflon AF nanopillars, as an electrostatic-based dry adhesive, is reported. The technique reported herein relies on the concurrent heating and cooling of the Teflon AF melt which filled vertically aligned alumina nanochannels as the mold. Unlike conventional polymer infiltration methods which consist of filling the mold by only heating the polymer above its glass transition temperature, in the current method, the polymer melt was also simultaneously cooled down during the infiltration process. Concurrent cooling of the Teflon AF melt allowed control over the interfacial instabilities of the polymer thin film, which formed ahead of the polymer melt upon its infiltration into the alumina nanochannels. By doing so, the geometrical properties of the peculiar fluffy nanostructure which was subsequently developed-after removal of the mold-on top of the extremely high aspect-ratio Teflon AF nanopillars (200 nm in diameter, ~25 µm tall) were modified. The height of the base nanopillars was measured and the structural properties (i.e., surface area fraction and roughness) of the fluffy nanostructure terminating the base nanopillars at the tip were quantified. Next, the effects of the topographical properties of the bi-level Teflon AF nanopillars on their adhesion, in both the normal and shear directions, were investigated. Tribological results were discussed in detail to clarify the contribution of the structural properties of the fabricated dry adhesive toward its remarkable adhesion and friction forces generated via contact electrification. It is worthwhile to mention that bi-level Teflon AF nanopillars with these specific structural properties have generated enhanced adhesion and friction strengths, up to ~2.1 and 13 N cm(-2), respectively.