“When an electric current flows through the system, the salty water divides into regions where the salt concentration is either depleted or enriched. When that current is increased to a certain point, it generates a shockwave between these two zones, sharply dividing the streams and allowing the fresh and salty regions to be separated by a simple physical barrier at the centre of the flow.”
Natural gas accounts for over 28 percent of US energy consumption. Its main component, methane, is a widely-used fossil fuel but also a major contributor to rising CO2 levels, and thus climate change. To address this issue, researchers from the Institute of Advanced Sustainability Studies (IASS) and Karlsruhe Institute of Technology (KIT) have developed a process that extracts the energy content of methane, in the form hydrogen, without producing carbon dioxide.
In a process called “methane cracking,” the molecular components of methane – hydrogen and carbon – are separated at temperatures of over 750° C (1,382° F), without harmful emissions. The concept of methane cracking has been around for several decades, but was limited by low conversion rates and carbon clogging.
The researchers have developed a material that allows high volumes of water to pass through extremely tiny holes called ‘nanopores’ while blocking salt and other contaminants. The material they’re using – a nanometre-thick sheet of molybdenum disulphide (MoS2) riddled with these nanopore holes – is the most efficient of a number of thin-film membranes that the engineers modelled, filtering up to 70 percent more water than graphene.
Finding naturally born young is evidence that conservation efforts are helping rebuild the islands ecosystem, which has been damaged, possibly irrevocably, since the 17th century.
Google has open sources their machine learning library. You are welcome.
TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.