Aquivion-Based Spray Freeze-Dried Composite Materials for the Cascade Production of γ-Valerolactone.

The development of multifunctional catalysts is a necessary step to effectively carry out one-pot cascade reactions, such as that from furfural to γ-valerolactone. This research effort faces the challenge posed by the intrinsic limit of how many kinds of catalytic sites a single material can bear. In this work, the application of Spray-Freeze Drying (SFD) as a synthetic technique for the preparation of a wide range of innovative composite multi-functional catalysts is reported. Herein we show that by the proper combination of Aquivion as a highly active Brønsted acid catalyst and metal oxides as both support materials and Lewis acids (LAS) enable to achieve highly unique efficient and effective dual acid composite catalysts that are able to carry out the cascade reaction from furfural to γ-valerolactone. The dual catalytic system comprised of Aq/ZrO2 with 30 % polymer content prepared via spray-freeze drying exhibited GVL yields of 25 % after only 2 h at 180 °C and a remarkably high productivity of 4470 µmolGVL gCat -1 h-1, one of the highest reported results. Mechanistic studies based on experimental and advanced characterisation and spectroscopic techniques, such as, SEM, TEM, 15N MAS NMR and 19F MAS NMR indicate that activity arises from the proper tuning of BAS/LAS (Brønsted Acid Site/Lewis Acid Site) acidic properties.

Design rules applied to silver nanoparticles synthesis: A practical example of machine learning application.

The synthesis of silver nanoparticles with controlled physicochemical properties is essential for governing their intended functionalities and safety profiles. However, synthesis process involves multiple parameters that could influence the resulting properties. This challenge could be addressed with the development of predictive models that forecast endpoints based on key synthesis parameters. In this study, we manually extracted synthesis-related data from the literature and leveraged various machine learning algorithms. Data extraction included parameters such as reactant concentrations, experimental conditions, as well as physicochemical properties. The antibacterial efficiencies and toxicological profiles of the synthesized nanoparticles were also extracted. In a second step, based on data completeness, we employed regression algorithms to establish relationships between synthesis parameters and desired endpoints and to build predictive models. The models for core size and antibacterial efficiency were trained and validated using a cross-validation approach. Finally, the features' impact was evaluated via Shapley values to provide insights into the contribution of features to the predictions. Factors such as synthesis duration, scale of synthesis and the choice of capping agents emerged as the most significant predictors. This study demonstrated the potential of machine learning to aid in the rational design of synthesis process and paves the way for the safe-by-design principles development by providing insights into the optimization of the synthesis process to achieve the desired properties. Finally, this study provides a valuable dataset compiled from literature sources with significant time and effort from multiple researchers. Access to such datasets notably aids computational advances in the field of nanotechnology.

Safe and sustainable by design Ag nanomaterials: A case study to evaluate the bio-reactivity in the environment using a soil model invertebrate.

Safe-and-sustainable-by-design (SSbD) nanomaterials (NMs) or NM-containing products are a priority. Silver (Ag) NMs have a vast array of applications, including biomedical and other products, even as nanopesticides. Thus, their release to the environment is expected to increase. The aim of the present study was to assess the ecotoxicity of the SSbD Ag NM to the soil model species Enchytraeus crypticus (Oligochaeta). The Ag NM tested consists in a SSbD Ag with biomedical applications, a hydroxyethyl cellulose (HEC) coated Ag NMs (AgHEC) and its toxicity was compared to the naked Ag NMs (Ag-Sigma), an Ag-based biomedical product (PLLA-Ag: Poly l-Lactide microfibers doped with Ag), and AgNO3. Effects were assessed both in soil and aqueous media, following the standard OECD guideline in soil (28 days) and the OECD extension (56 days), and short-term pulse (5 days) in aqueous media: reconstituted water (ISO water) and soil:water (S:W) extracts, followed by a 21-days recovery period in soil. Ag materials were thoroughly characterized as synthesized and during the test in media and animals. Results in S:W showed AgHEC was more toxic than Ag-Sigma (ca. 150 times) and PLLA-Ag (ca. 2.5 times), associated with a higher Ag uptake. Higher toxicity was related to a smaller hydrodynamic size and higher suspension stability, which in turn resulted in a higher bioavailability of Ag NMs and released ions, particularly in S:W. Toxicity was correlated with the main physicochemical features, providing useful prediction of AgNMs bioactivity. The ability to test E. crypticus in a range of media with different and/or increasing complexity (water, S:W extracts, soil) provided an excellent source to interpret results and is here recommended.