library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be m z obtained from experimental measurements ( / , CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large data set of m z in silico structures with / labels. Next, property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller data sets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Collini, H., Li, S., Jackson, M.D., Agenet, N., Rashid, B., Couves, J., 2020. Zeta potential in intact carbonates at reservoir conditions and its impact on oil recovery during controlled salinity waterflooding. Fuel 266, 116927.

http://www.sciencedirect.com/science/article/pii/S0016236119323208 It is well known that oil recovery from carbonate reservoirs can be increased by modifying the injected brine composition in a process 'controlled salinity water - flooding' (CSW). However, the mineral - to pore- scale processes responsible for improved oil recovery (IOR) during CSW remain ambiguous and there is no method to predict the optimum CSW composition for a given crude-oil-brine rock system. Here we report the first integrated experimental measurements of zeta potential and IOR during CSW obtained at reservoir conditions. The zeta potential is a measure of the electrical potential at mineral-brine and oil-brine interfaces and controls the electrostatic forces acting between these interfaces. We find that the measured zeta potential in clean samples saturated with formation brine is typically positive and becomes more negative with brine dilution irrespective of temperature. After aging and wettability alteration, the zeta potential changes and we suggest a more positive zeta potential indicates a positive zeta potential at the oil-brine interface and vice-versa. Injecting low salinity brine yields IOR when the oil-brine zeta potential is identified to be negative, but no response when it is identified to be positive, consistent with the hypothesis that IOR during CSW is caused by an increase in the repulsive electrostatic force acting between mineral-brine and oil-brine interfaces. We suggest that the optimum brine composition for IOR during CSW should be chosen to yield the largest change in zeta potential at the mineral-brine interface with opposing polarity to the oil-brine interface and can be determined using the experimental method reported here.

Contador, C.A., Veas-Castillo, L., Tapia, E., Antipán, M., Miranda, N., Ruiz-Tagle, B., García-Araya, J., Andrews, B.A., Marin, M., Dorador, C., Asenjo, J.A., 2020. Atacama Database: a platform of the microbiome of the Atacama Desert. Antonie van Leeuwenhoek 113, 185-195.

https://doi.org/10.1007/s10482-019-01328-x The Atacama Desert is one of the oldest and driest places on Earth. In the last decade, microbial richness and diversity has been acknowledged as an important biological resource of this region. Owing to the value of the microbial diversity apparent in potential biotechnology applications and conservation purposes, it is necessary to catalogue these microbial communities to promote research activities and help to preserve the wide range of ecological niches of the Atacama region. A prototype Atacama Database has been designed and it provides a description of the rich microbial diversity of the Atacama Desert, and helps to visualise available literature resources. Data has been collected, curated, and organised into several categories to generate a single record for each organism in the database that covers classification, isolation metadata, morphology, physiology, genome and metabolism information. The current version of Atacama Database contains 2302 microorganisms and