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New research has characterized how a dissolved polymer chain responds to suddenly accelerating solvent flow, solving a long-standing polymer chemistry puzzle.

Researchers have fabricated a multisensory neuron by connecting a tactile sensor to a phototransistor based on a monolayer of molybdenum disulfide. The sensor allows the integration of both visual and tactile cues.

AI systems are often built using artificial neural networks (ANN) analogous to those of the brain. Like the brain, ANNs can sometimes get confused, either by accident or by the deliberate actions of a third party. Researchers have now devised and tested a new way to improve ANN defense.

The Demand.ninja model, created by researchers at Imperial College London and TU Delft, was designed to show how the weather influences hourly energy consumption in buildings.

Scientists using machine learning tools to analyze biomedical data often turn to neural network algorithms, but before these models became popular, another simpler type of machine learning algorithm called kernel methods were commonly used.

By developing an efficient way to compare all predicted protein structures in the AlphaFold database, researchers have revealed similarities between proteins across different species.

Many of the bacteria that ravage crops and threaten our food supply use a common strategy to cause disease: injecting a cocktail of proteins directly into the plant’s cells. Now researchers may finally have an answer to how this makes plants sick.

Oceans are strongly affected by climate change as they absorb heat and CO₂. As a result, ocean chemistry and acidification is changing.

Antibody treatments may be able to activate the immune system to fight diseases but are less effective when they bind with themselves. Now, new machine-learning algorithms can highlight problem areas in antibodies.

An approach to training AI that relies on physical processes rather than the digital artificial neural networks used currently could be more efficient.