Freeform Optics for Imaging: Design Methods | Webinars photonics.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from photonics.com Daily Mail and Mail on Sunday newspapers.
New catalyst for oxidative dehydrogenation of propane to propylene
This company’s Insights platform is connected to the new temperature…
By Scott Jenkins |
May 1, 2021
Conventional propane dehydrogenation (PDH) is an endothermic, equilibrium-limited reaction that requires high temperatures to achieve commercially viable per-pass yields of propylene. Oxidative propane dehydrogenation has the potential to form propylene at much lower temperatures and more selectively by controlling the reaction kinetically, rather than thermodynamically. However, it has proven difficult to prevent large amounts of propane combustion and to generate sufficient amounts of propylene.
A new tandem catalyst designed and developed by researchers at Northwestern University (Evanston, Ill.; www.northwestern.edu) has generated good results in oxidatively dehydrogenating propane to propylene at selectivities of 75% and single-pass propane conversion rates of 40% at temperatures of 450°C (compared to ~
by Tracey Peake April 30, 2021 .
RALEIGH – Every spring, researchers publish their projected forecasts of the upcoming hurricane season – how many storms may form, and how severe they may be. But what if you could create these forecasts up to a year and a half in advance? A new model from North Carolina State University incorporates machine learning to create long-range hurricane forecasts with similar accuracy to those currently in use.
Most preseason hurricane predictions are made using statistical models that utilize optimized data from sea level pressure, sea surface temperatures and other historical climatic data. However, these predictions are made from time series data – meaning that they use climatic readings from one location or averaged over a particular area and time period.
Date Time
Model Could Create Hurricane Forecasts up to 18 Months in Advance
Every spring, researchers publish their projected forecasts of the upcoming hurricane season – how many storms may form, and how severe they may be. But what if you could create these forecasts up to a year and a half in advance? A new model from North Carolina State University incorporates machine learning to create long-range hurricane forecasts with similar accuracy to those currently in use.
Most preseason hurricane predictions are made using statistical models that utilize optimized data from sea level pressure, sea surface temperatures and other historical climatic data. However, these predictions are made from time series data – meaning that they use climatic readings from one location or averaged over a particular area and time period.
Nanotechnology Now
Our NanoNews Digest Sponsors
Home > Press > Nanoparticle drug delivery technique shows promise for treating pancreatic cancer: Method may also work for breast, prostate, ovarian cancer
Study researchers Drs. Snigdha Banerjee, Suman Kambhampati, Sushanta Banerjee, and a colleague examine a pancreatic cancer image.
CREDIT
Jeff Gates
Abstract:
Researchers with the Kansas City Veterans Affairs Medical Center and North Dakota State University have designed a new way to deliver pancreatic cancer drugs that could make fighting the disease much easier. Encapsulating cancer drugs in nanoparticles shows potential to target tumors more effectively and avoid danger to other parts of the body.