Sometimes, chemical reactions do not solely run stationary in one direction, but they show spatio-temporal oscillations. Scientists have now observed a transition to chaotic behavior on the nanometer scale.
A new form of heterostructure of layered two-dimensional (2D) materials may enable quantum computing to overcome key barriers to its widespread application, according to an international team of researchers.
Researchers have discovered that channeling ions into defined pathways in perovskite materials improves the stability and operational performance of perovskite solar cells.
RNA nanosatellite leads researchers to the discovery of rules and mechanisms for RNA folding that will make it possible to build more ideal and functional RNA particles for use in RNA-based medicine.
By illuminating a sample surface with short laser beam pulses, it is possible to film sequences of various chemical and physical reactions. A research team has now developed the world's fastest single-shot laser camera, which is at least a thousand times faster than today's most modern equipment for combustion diagnostics.
Researchers have developed a new device that can detect and analyse cancer cells from blood samples, enabling doctors to avoid invasive biopsy surgeries, and to monitor treatment progress.
Researchers used an electro-photonic tweezer along with metal nanoparticles to concentrate ultrafine nanoplastics within a short period, and they reported the development of a real-time detection system using light.
Perovskite solar cells (PSCs) are complex devices made up of multiple materials that have many different factors affecting their properties, which makes it difficult to analyze them comprehensively. Machine Learning (ML) can efficiently handle these complexities and help scientists in the design of new PSCs. We outline the current state and future prospects of ML in perovskite solar cell research, including data sources, feature extraction, algorithms, model validation, interpretation, ...
