Inverse design is an outstanding challenge in disordered systems with multiple length scales such as polymers, particularly when designing polymers with desired phase behavior. We demonstrate high-accuracy tuning of poly(2-oxazoline) cloud point via machine learning. With a design space of four repeating units and a range of molecular masses, we achieve an accuracy of 4°C root mean squared error (RMSE) in a temperature range of 24-90°C, employing gradient boosting with decision trees. The RMSE is >3x better than linear and polynomial regression. We perform inverse design via particle-swarm optimization, predicting and synthesizing 17 polymers with constrained design at 4 target cloud points from 37 to 80°C. Our approach challenges the status quo in polymer design with a machine learning algorithm, that is capable of fast and systematic discovery of new polymers.

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Lanthanum phosphate (LaP) nano-rods were synthesized using n-butylamine as a shape-directing agent (SDA). The resulting catalysts were applied in the dehydration of lactic acid to acrylic acid. Aiming to understand the nature of the active sites, the chemical and physical properties of LaP materials were studied using a variety of characterization techniques. This study showed that the SDA not only affected the porosity of the LaP materials but also modified the acid-base properties. Clearly, the modification of the acid-base properties played a more critical role in determining the catalytic performance than porosity. An optimized catalytic performance was obtained on the LaP catalyst with a higher concentration of Lewis acid sites. Basic sites showed negative effects on the stability of the catalysts. Good stability was achieved when the catalyst was prepared using the appropriate SDA/La ratio.

Polymeric hydrogels are promising biomaterials to be used as vitreous tamponade in the eye. However, while the clinical need and the required attributes of a vitreous replacement hydrogel are clear, there is a major gap in understanding the various polymer requirements to achieve the “ideal” hydrogel. In this study, we investigated the effect of the polymer molecular weight on polyurethane thermogel properties and found that there is a theoretical minimum number of hydrophobic blocks required for gelation. We then used these polymers as vitreous replacements. We found that there is a preferred molecular weight range, whereby hydrogels with lower molecular weights can cause retinal atrophy and corresponding functional visual loss, while those with higher molecular weights lead to opacity issues. Thermogels in the preferred molecular weight range retained the normal retinal structure and exhibited full visual recovery within 3 months. The effect of the molecular weight was further demonstrated by the effects of postsynthetic autoclaving on the retinal structure and function. The effect of the polymer molecular weight on the functional characteristics of hydrogels demonstrated herein is an important design parameter for polymeric hydrogels for ocular applications.