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Hydrophobic and Hydrophilic Interactions

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Self-assembled Janus plasmene nanosheets as flexible 2D photocatalysts.

Materials horizons
A leaf is a free-standing photocatalytic system that can effectively harvest solar energy and convert CO and HO into carbohydrates in a continuous manner without the need for regeneration or tedious product extraction steps. Despite encouraging advan...

Prediction of the chromatographic hydrophobicity index with immobilized artificial membrane chromatography using simple molecular descriptors and artificial neural networks.

Journal of chromatography. A
Screening of physicochemical properties should be considered one of the essential steps in the drug discovery pipeline. Among the available methods, biomimetic chromatography with an immobilized artificial membrane is a powerful tool for simulating i...

Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data.

Analytical chemistry
Machine learning is a popular technique to predict the retention times of molecules based on descriptors. Descriptors and associated labels (e.g., retention times) of a set of molecules can be used to train a machine learning algorithm. However, desc...

Identifying nonadditive contributions to the hydrophobicity of chemically heterogeneous surfaces via dual-loop active learning.

The Journal of chemical physics
Hydrophobic interactions drive numerous biological and synthetic processes. The materials used in these processes often possess chemically heterogeneous surfaces that are characterized by diverse chemical groups positioned in close proximity at the n...

automRm: An R Package for Fully Automatic LC-QQQ-MS Data Preprocessing Powered by Machine Learning.

Analytical chemistry
Preprocessing of liquid chromatography-mass spectrometry (LC-MS) raw data facilitates downstream statistical and biological data analyses. In the case of targeted LC-MS data, consistent recognition of chromatographic peaks is a main challenge, in par...

Bioinspired Self-Resettable Hydrogel Actuators Powered by a Chemical Fuel.

ACS applied materials & interfaces
The movements of soft living tissues, such as muscle, have sparked a strong interest in the design of hydrogel actuators; however, so far, typical manmade examples still lag behind their biological counterparts, which usually function under nonequili...

Prediction of the Lotus Effect on Solid Surfaces by Machine Learning.

Small (Weinheim an der Bergstrasse, Germany)
Superhydrophobic surfaces with the "lotus effect" have wide applications in daily life and industry, such as self-cleaning, anti-freezing, and anti-corrosion. However, it is difficult to reliably predict whether a designed superhydrophobic surface ha...

Surface-enhanced Raman spectroscopy charged probes under inverted superhydrophobic platform for detection of agricultural chemicals residues in rice combined with lightweight deep learning network.

Analytica chimica acta
In this study, surface-enhanced Raman spectroscopy (SERS) charged probes and an inverted superhydrophobic platform were used to develop a detection method for agricultural chemicals residues (ACRs) in rice combined with lightweight deep learning netw...

Machine learning and classical MD simulation to identify inhibitors against the P37 envelope protein of monkeypox virus.

Journal of biomolecular structure & dynamics
Monkeypox virus (MPXV) outbreak is a serious public health concern that requires international attention. P37 of MPXV plays a pivotal role in DNA replication and acts as one of the promising targets for antiviral drug design. In this study, we intent...

Role of environmental specificity in CASP results.

BMC bioinformatics
BACKGROUND: Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Predict...