Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks.

The critical micelle concentration (CMC) of surfactant molecules is an essential property for surfactant applications in the industry. Recently, classical quantitative structure-property relationship (QSPR) and graph neural networks (GNNs), a deep learning technique, have been successfully applied to predict the CMC of surfactants at room temperature. However, these models have not yet considered the temperature dependence of the CMC, which is highly relevant to practical applications. We herein develop a GNN model for the temperature-dependent CMC prediction of surfactants. We collected about 1400 data points from public sources for all surfactant classes, i.e., ionic, nonionic, and zwitterionic, at multiple temperatures. We test the predictive quality of the model for the following scenarios: (i) when CMC data for surfactants are present in the training of the model in at least one different temperature and (ii) CMC data for surfactants are not present in the training, i.e., generalizing to unseen surfactants. In both test scenarios, our model exhibits a high predictive performance of R2 ≥ 0.95 on test data. We also find that the model performance varies with the surfactant class. Finally, we evaluate the model for sugar-based surfactants with complex molecular structures, as these represent a more sustainable alternative to synthetic surfactants and are therefore of great interest for future applications in the personal and home care industries.

Innovative digital solution supporting sun protection and vitamin D synthesis by using satellite-based monitoring of solar radiation.

Public health campaigns advise minimising UV radiation (UVR) exposure to prevent skin cancer and precancer, e.g. actinic keratosis (AK). A 3-day clinical field study, in Brazil, was performed to evaluate the mobile app Sun4Health® by siHealth Ltd. The app performs real-time monitoring of both erythemal and vitamin D-effective solar radiation doses using satellite data, enabling personalised recommendations on optimal sun exposure time and sunscreen use. When coupled to a wearable device, the app also provides body-site specific recommendations ("3D" version). 59 healthy volunteers were randomised into 3 groups, each given a different app providing: (1) ultraviolet index only (control app), (2) personalised recommendations and sun overexposure alerts (Sun4Health® app), (3) as (2) but connected via Bluetooth to a wearable device to monitor sun exposure in 3D (Sun4Health®-3D app). Participants were offered sunscreens (SPF 30 and 50) to use at their discretion. Erythema, quantified by reflectance spectroscopy, was assessed daily in the mornings and evenings on six body sites. Serum vitamin D (25(OH)D3) was measured before and after the study. Mean increase of erythema (Mexameter® units ± SD) of all exposed body sites combined over 3 days showed 55.76 ± 47.47 for group 1, 40.27 ± 37.91 for group 2 and 37.12 ± 30.69 for group 3 (p < 0.05 for all groups). Mean increase of serum 25(OH)D3 (nmol/l ± SD) showed 1.32 ± 36.49 for group 1, 6.38 ± 21.19 for group 2 and 18.68 ± 35.45 for group 3 (p > 0.05 for all groups). The results show that the Sun4Health® app is safe to use and can modify behaviour to reduce skin erythema (sunburn) yet not decreasing vitamin D status.

Direct spectrophotometric assay for benzaldehyde lyase activity.

Benzaldehyde lyase from Pseudomonas fluorescens Biovar I. (BAL, EC 4.1.2.38) is a versatile catalyst for the organic synthesis of chiral α-hydroxy ketones. To allow fast assessment of enzyme activity, a direct spectrophotometric assay is desirable. Here, a new robust and easy-to-handle assay based on UV absorption is presented. The assay developed is based on the ligation of the α-hydroxy ketone (R)-2,2'-furoin from 2-furaldehyde. A robust assay with direct monitoring of the product is facilitated with a convenient concentration working range minimising experimental associated with low concentrations.

Ionic liquids as performance additives for electroenzymatic syntheses.

Electroenzymatic syntheses combine oxidoreductase-catalysed reactions with electrochemical reactant supply. The use of ionic liquids as performance additives can contribute to overcoming existing limitations of these syntheses. Here, we report on the influence of different water-miscible ionic liquids on critical parameters such as conductivity, biocatalyst activity and stability or substrate solubility for three typical electroenzymatic syntheses. In these investigations promising ionic liquids were identified and have been used as additives for batch electrolyses on preparative scale for the three electroenzymatic systems. It was possible to improve the space-time-yield for the electrochemical regeneration of NADPH by a factor of three. For an amino acid oxidase catalysed resolution of a methionine racemate with ferrocene-mediated electrochemical regeneration of the enzyme-bound cofactor FAD a 50% increase in space time yield and 140% increase in catalyst utilisation (TTN) were achieved. Furthermore, for the chloroperoxidase-catalysed synthesis of (R)-phenylmethylsulfoxide with electrochemical generation of the required cosubstrate H2O2 the space time yield and the catalyst utilisation were improved by a factor of up to 4.2 depending on the ionic liquids used.