Unique Method for Facile Postsynthetic Modification of Nonisocyanate Polyurethanes.

Nonisocyanate polyurethanes (NIPUs) are broadly investigated as a potential replacement for conventional polyurethanes (PUs) to eliminate the use of toxic isocyanates and reduce occupational hazards. One of the most popular approaches to NIPU synthesis is the polyaddition of cyclic bis(carbonate)s and diamines to form poly(hydroxyurethane)s (PHUs). However, such PHUs are highly hydrophilic due to the presence of two hydroxyl groups per repeat unit, and the resulting moisture absorption significantly degrades their thermomechanical performance and physical stability upon exposure to humidity, thus limiting their utility. Here, we introduce a simple and scalable approach for the modification of PHUs to increase hydrophobicity and adjust their properties. The proposed reaction between aldehydes and appropriately spaced hydroxyl groups in the polymer backbone resulted in high degrees of modification (up to 84%) and up to 3-fold reductions in water uptake at 85% RH. Furthermore, the use of aromatic aldehydes in particular enabled the retention of mechanical properties over a wide range of humidity levels, resulting in performance comparable to conventional PUs. Finally, we note that this approach is not limited to reducing moisture sensitivity alone and provides ample opportunities for imparting a broad range of novel properties to PHUs through an appropriate selection of functional aldehydes.

4D Printing of Electroactive Triple-Shape Composites.

Triple-shape polymers can memorize two independent shapes during a controlled recovery process. This work reports the 4D printing of electro-active triple-shape composites based on thermoplastic blends. Composite blends comprising polyester urethane (PEU), polylactic acid (PLA), and multiwall carbon nanotubes (MWCNTs) as conductive fillers were prepared by conventional melt processing methods. Morphological analysis of the composites revealed a phase separated morphology with aggregates of MWCNTs uniformly dispersed in the blend. Thermal analysis showed two different transition temperatures based on the melting point of the crystallizable switching domain of the PEU (Tm~50 ± 1 °C) and the glass transition temperature of amorphous PLA (Tg~61 ± 1 °C). The composites were suitable for 3D printing by fused filament fabrication (FFF). 3D models based on single or multiple materials were printed to demonstrate and quantify the triple-shape effect. The resulting parts were subjected to resistive heating by passing electric current at different voltages. The printed demonstrators were programmed by a thermo-mechanical programming procedure and the triple-shape effect was realized by increasing the voltage in a stepwise fashion. The 3D printing of such electroactive composites paves the way for more complex shapes with defined geometries and novel methods for triggering shape memory, with potential applications in space, robotics, and actuation technologies.

In vivo detection of head and neck tumors by hyperspectral imaging combined with deep learning methods.

Currently, there are no fast and accurate screening methods available for head and neck cancer, the eighth most common tumor entity. For this study, we used hyperspectral imaging, an imaging technique for quantitative and objective surface analysis, combined with deep learning methods for automated tissue classification. As part of a prospective clinical observational study, hyperspectral datasets of laryngeal, hypopharyngeal and oropharyngeal mucosa were recorded in 98 patients before surgery in vivo. We established an automated data interpretation pathway that can classify the tissue into healthy and tumorous using convolutional neural networks with 2D spatial or 3D spatio-spectral convolutions combined with a state-of-the-art Densenet architecture. Using 24 patients for testing, our 3D spatio-spectral Densenet classification method achieves an average accuracy of 81%, a sensitivity of 83% and a specificity of 79%.

Adhesion Optimization between Incompatible Polymers through Interfacial Engineering.

Additive manufacturing technologies such as fused filament fabrication (FFF) open many possibilities in terms of product functionality, including the possibility to integrate a sensor in FFF parts to perform structural health monitoring. In this context, embedding fiber Bragg grating (FBG) sensors into 3D-printed polymeric structures for strain or temperature measurements has attracted increasing attention in recent years. Indeed, offering structural health monitoring functionality can optimize the maintenance cost and increase security compared with conventional materials. However, the transmission of strain and temperature between the polymeric matrix and the FBG polymer jacket requires optimal bonding between them. In this work, the two polymers of interest are polyimide (PI) and poly(lactic acid) (PLA) for the FBG jacket and printed polymer, respectively. The current study investigates the influence of different surface treatment methods on the adhesion between a PI film and a plate of PLA, with PLA and PI being incompatible polymers. The adhesion promotion applied to the PI surface relies on cleaning, plasma activation, roughness modification, or the use of adhesive nanocoating. Bilayer samples of PI-PLA are processed by welding PLA against the treated PI by heating, whereas the adhesion between PI and PLA is measured by peel testing. It is observed that the highest adhesion between PI and PLA is achieved by a combination of mechanical abrasion increasing roughness and the use of polydopamine as an adhesive. This finding is discussed based on a synergetic effect between mechanical interlocking and chemical interaction between the two counterfaces.

Influence of Silica Specific Surface Area on the Viscoelastic and Fatigue Behaviors of Silica-Filled SBR Composites.

This work aimed at studying the effect of a silica specific surface area (SSA), as determined by the nitrogen adsorption method, on the viscoelastic and fatigue behaviors of silica-filled styrene-butadiene rubber (SBR) composites. In particular, silica fillers with an SSA of 125 m2/g, 165 m2/g, and 200 m2/g were selected. Micro-computed X-ray tomography (µCT) was utilized to analyze the 3D morphology of the fillers within an SBR matrix prior to mechanical testing. It was found with this technique that the volume density of the agglomerates drastically decreased with decreasing silica SSA, indicating an increase in the silica dispersion state. The viscoelastic behavior was evaluated by dynamic mechanical analysis (DMA) and hysteresis loss experiments. The fatigue behavior was studied by cyclic tensile loading until rupture enabled the generation of Wöhler curves. Digital image correlation (DIC) was used to evaluate the volume strain upon deformation, whereas µCT was used to evaluate the volume fraction of the fatigue-induced cracks. Last, scanning electron microscopy (SEM) was used to characterize, in detail, crack mechanisms. The main results indicate that fatigue life increased with decreasing silica SSA, which was also accompanied by a decrease in hysteresis loss and storage modulus. SEM investigations showed that filler-matrix debonding and filler fracture were the mechanisms at the origin of crack initiation. Both the volume fraction of the cracks obtained by µCT and the volume strain acquired from the DIC increased with increasing SSA of silica. The results are discussed based on the prominent role of the filler network on the viscoelastic and fatigue damage behaviors of SBR composites.

Reinforcement of Styrene Butadiene Rubber Employing Poly(isobornyl methacrylate) (PIBOMA) as High Tg Thermoplastic Polymer.

A set of poly(isobornyl methacrylate)s (PIBOMA) having molar mass in the range of 26,000-283,000 g mol-1 was prepared either via RAFT process or using free radical polymerization. These linear polymers demonstrated high glass transition temperatures (Tg up to 201 °C) and thermal stability (Tonset up to 230 °C). They were further applied as reinforcing agents in the preparation of the vulcanized rubber compositions based on poly(styrene butadiene rubber) (SBR). The influence of the PIBOMA content and molar mass on the cure characteristics, rheological and mechanical properties of rubber compounds were studied in detail. Moving die rheometry revealed that all rubber compounds filled with PIBOMA demonstrated higher torque increase values ΔS in comparison with rubber compositions without filler, independent of PIBOMA content or molar mass, thus confirming its reinforcing effect. Reinforcement via PIBOMA addition was also observed for vulcanized rubbers in the viscoelastic region and the rubbery plateau, i.e. from -20 to 180 °C, by dynamic mechanical thermal analysis. Notably, while at temperatures above ~125 °C, ultra-high-molecular-weight polyethylene (UHMWPE) rapidly loses its ability to provide reinforcement due to softening/melting, all PIBOMA resins maintained their ability to reinforce rubber matrix up to 180 °C. For rubber compositions containing 20 phr of PIBOMA, both tensile strength and elongation at break decreased with increasing PIBOMA molecular weight. In summary, PIBOMA, with its outstanding high Tg among known poly(methacrylates), may be used in the preparation of advanced high-stiffness rubber compositions, where it provides reinforcement above 120 °C and gives properties appropriate for a range of applications.

Fused Filament Fabrication of Polymers and Continuous Fiber-Reinforced Polymer Composites: Advances in Structure Optimization and Health Monitoring.

3D printed neat thermoplastic polymers (TPs) and continuous fiber-reinforced thermoplastic composites (CFRTPCs) by fused filament fabrication (FFF) are becoming attractive materials for numerous applications. However, the structure of these materials exhibits interfaces at different scales, engendering non-optimal mechanical properties. The first part of the review presents a description of these interfaces and highlights the different strategies to improve interfacial bonding. The actual knowledge on the structural aspects of the thermoplastic matrix is also summarized in this contribution with a focus on crystallization and orientation. The research to be tackled to further improve the structural properties of the 3D printed materials is identified. The second part of the review provides an overview of structural health monitoring technologies relying on the use of fiber Bragg grating sensors, strain gauge sensors and self-sensing. After a brief discussion on these three technologies, the needed research to further stimulate the development of FFF is identified. Finally, in the third part of this contribution the technology landscape of FFF processes for CFRTPCs is provided, including the future trends.

Decoupling the Contributions of ZnO and Silica in the Characterization of Industrially-Mixed Filled Rubbers by Combining Small Angle Neutron and X-Ray Scattering.

Scattering techniques with neutrons and X-rays are powerful methods for the investigation of the hierarchical structure of reinforcing fillers in rubber matrices. However, when using only X-ray scattering, the independent determination of the filler response itself sometimes remains an issue because of a strong parasitic contribution of the ZnO catalyst and activator in the vulcanization process. Microscopic characterization of filler-rubber mixtures even with only catalytic amounts of ZnO is, therefore, inevitably complex. Here, we present a study of silica aggregates dispersed in an SBR rubber in the presence of the catalyst and show that accurate partial structure factors of both components can be determined separately from the combination of the two scattering probes, neutrons, and X-rays. A unique separation of the silica filler scattering function devoid of parasitic catalyst scattering becomes possible. From the combined analysis, the catalyst contribution is determined as well and results to be prominent in the correction scheme. The experimental nano-structure of the ZnO after the mixing process as the by-product of the scattering decomposition was found also to be affected by the presence or absence of silica in the rubber mixture, correlated with the shear forces in the mixing and milling processes during sample preparation. The presented method is well suited for studies of novel dual filler systems.

Hyperspectral Imaging Using Flexible Endoscopy for Laryngeal Cancer Detection.

Hyperspectral imaging (HSI) is increasingly gaining acceptance in the medical field. Up until now, HSI has been used in conjunction with rigid endoscopy to detect cancer in vivo. The logical next step is to pair HSI with flexible endoscopy, since it improves access to hard-to-reach areas. While the flexible endoscope's fiber optic cables provide the advantage of flexibility, they also introduce an interfering honeycomb-like pattern onto images. Due to the substantial impact this pattern has on locating cancerous tissue, it must be removed before the HS data can be further processed. Thereby, the loss of information is to minimize avoiding the suppression of small-area variations of pixel values. We have developed a system that uses flexible endoscopy to record HS cubes of the larynx and designed a special filtering technique to remove the honeycomb-like pattern with minimal loss of information. We have confirmed its feasibility by comparing it to conventional filtering techniques using an objective metric and by applying unsupervised and supervised classifications to raw and pre-processed HS cubes. Compared to conventional techniques, our method successfully removes the honeycomb-like pattern and considerably improves classification performance, while preserving image details.

Development of an image pre-processor for operational hyperspectral laryngeal cancer detection.

Hyperspectral imaging (HSI) is a technology with high potential in the field of non-invasive detection of cancer. However, in complex imaging situations like HSI of the larynx with a rigid endoscope, various image interferences can disable a proper classification of cancerous tissue. We identified three main problems: i) misregistration of single images in a HS cube due to patient heartbeat ii) image noise and iii) specular reflections (SR). Consequently, an image pre-processor is developed in the current paper to overcome these image interferences. It encompasses i) image registration ii) noise removal by minimum noise fraction (MNF) transformation and iii) a novel SR detection method. The results reveal that the pre-processor improves classification performance, while the newly developed SR detection method outperforms global thresholding technique hitherto used by 46%. The novel pre-processor will be used for future studies towards the development of an operational scheme for HS-based larynx cancer detection. RGB image of the larynx derived from the hyperspectral cube and corresponding specular reflections (a) manually segmented and (b) detected by a novel specular reflection detection method.