Jose Enrico Quijano Quinsaat

Bio-based alternatives to conventional rigid foams have proven to be good substitutes owing to their enhanced sustainability and competitive performance. However, because their manufacturing processes are complex and destructive testing is often impractical, this study investigates whether microstructural features can be correlated with mechanical properties in lignin-containing rigid polyurethane (PU) foams using machine learning approaches. Various types and percentages of lignin-based polyols were investigated as partial replacements for polyol, including LHO, DCA, DCA-D, LHO-O, Kraft lignin (KL), and LHO-MD, at polyol replacement levels ranging from 12.5% to 50%, together with a control formulation. Scanning electron microscopy (SEM) images and corresponding mechanical compression data were used to train a custom state-of-the-art dual-head convolutional neural network (CNN) targeting the specific prediction of density, specific compression modulus, specific yield stress, and specific compression strength. The CNN was optimized with a weighted multi-output loss function, achieving strong predictive performance with R² values ranging from 0.850 to 0.91 and correlation coefficients above 0.92, while maintaining mean absolute error percentages below ≈9%. This proves the trained network’s capability to predict and capture morphological features governing load-bearing responses. On the other hand, Grad-CAM visualization revealed that the network focused its predictions on physically meaningful microstructural regions such as cell walls and strut junctions, which confirms that the proposed network can be classified as an interpretable, non-destructive, and data-driven framework for predicting and understanding bio-based PU foams’ mechanical behavior, hence reducing the inconvenience caused by time-consuming manufacturing and destructive testing.

Silver nanoparticles (AgNPs) are used in a wide range of applications, and the size control and stability of the nanoparticles are crucial aspects in their applications. In the present study, cyclized poly(ethylene glycol) (c-PEG) with various molecular weights, along with linear PEG with hydroxy chain ends (HO–PEG–OH) and methoxy chain ends (MeO–PEG–OMe) were applied for the Tollens’ synthesis of AgNPs. The particle size was significantly affected by the topology and end groups of PEG. For example, the size determined by TEM was 40 ± 7 nm for HO–PEG_5k–OH, 21 ± 4 nm for c-PEG_5k, and 48 ± 9 nm for MeO–PEG_5k–OMe when the molar ratio of PEG to AgNO₃ (ω) was 44. The stability of AgNPs was also drastically improved by cyclization; the relative UV–Vis absorption intensity (A/A₀ × 100%) at λ_max to determine the proportion of persisting AgNPs in an aqueous NaCl solution (37.5 mM) was 58% for HO–PEG_5k–OH, 80% for c-PEG_5k, and 40% for MeO–PEG_5k–OMe, despite the fact that AgNPs with c-PEG_5k were much smaller than those with HO–PEG_5k–OH and MeO–PEG_5k–OMe.

Polyurethane polymers are found in a wide range of material applications. However, the toxic nature of isocyanates used in their formulation is a major concern; hence, more environmentally friendly alternatives are of high interest in the search for new sustainable polymer materials. In this work, we present the preparation of isocyanate-free polyurethane/epoxy hybrid thermosets with a high biobased content (85-90 wt %). The isocyanate-free polyurethanes were based on polyhydroxyurethanes (PHUs) prepared from depolymerized native lignin, which we refer to as lignin hydrogenolysis oil (LHO). The LHO was functionalized with epichlorohydrin to yield the epoxidized structure (LHO-GE), which was in turn reacted with CO₂ to form the cyclocarbonated species (LHO-CC). Blends of the LHO-CC and glycerol diglycidyl ether (GDGE) were cured to produce hybrid PHU/epoxy (LHO-CC/GDGE) thermosets. Thermosetting materials with flexural moduli of 4.5 GPa and flexural strengths of 160 MPa were produced by optimizing the mass ratio of the two main components and the triamine hardener. These novel biobased hybrid materials outperformed the corresponding epoxy-only thermosets and comparable hybrid PHU/epoxy materials produced from petrochemicals.

Nano-sized metal particles are attracting much interest in industrial and biomedical applications due to the recent progress and development of nanotechnology, and the surface-modifications by appropriate polymers are key techniques to stably express their characteristics. Herein, we applied cyclic poly(ethylene glycol) (c-PEG), having no chemical inhomogeneity, to provide a polymer topology-dependent stabilization for the surface-modification of gold nanoparticles (AuNPs) through physisorption. By simply mixing c-PEG, but not linear counterparts, enables AuNPs to maintain dispersibility through freezing, lyophilization, or heating. Surprisingly, c-PEG endowed AuNPs with even better dispersion stability than thiolated PEG (HS–PEG–OMe). The stronger affinity of c-PEG was confirmed by DLS, ζ-potential, and FT-IR. Furthermore, the c-PEG system exhibited prolonged blood circulation and enhanced tumor accumulation in mice. Our data suggests that c-PEG induces physisorption on AuNPs, supplying sufficient stability toward bio-medical applications, and would be an alternative approach to the gold–sulfur chemisorption.