New Worlds: Nanoscale catalysts show ‘defects’ are useful

The process by which a catalyst accelerates a chemical reaction is key to the creation of many materials essential to daily life

A scientist looks through a microscope (photo credit: INGIMAGE)
A scientist looks through a microscope
(photo credit: INGIMAGE)
Using one of the world’s brightest light sources to peer inside some of the world’s smallest particles, scientists have confirmed a longstanding hypothesis – that atomic disorder or “defects” at the edges of nanoparticles is what makes them effective as chemical change agents (catalysts).
The process by which a catalyst accelerates a chemical reaction is key to the creation of many materials essential to daily life, such as plastics, fuels and fertilizers. Known as catalysis, this process is a basic pillar of the chemical industry, making chemical reactions more efficient and less energy-demanding, reducing or even eliminating the use and generation of hazardous substances.
Published in the prestigious journal Nature, the study validates the hypothesis that atomic defects are essential to catalytic reactivity. In addition, it showed improved catalysts can make chemical processes greener by decreasing energy use and preventing formation of hazardous products.
Although catalysts have been used in industry for more than a century, scientists have yet to observe how their structure impacts their effectiveness as change agents. That’s because catalysts are typically tiny metallic nanoparticles made of precious metals. The extreme smallness that makes nanoparticles such effective catalysts also makes it hard to see how they work.
If scientists could peer inside individual nanoparticle chemical reactions at a nanoscopic level, they would gather a treasure of useful knowledge for the design of improved catalysts to address the pressing energy needs of the 21st century.
That type of knowledge may now be close at hand, thanks to the new Israeli study led by Dr. Elad Gross from the Hebrew University’s institute of chemistry and the center for nanoscience and nanotechnology, and Prof. F. Dean Toste from the College of Chemistry at the University of California, Berkeley and chemical science division at Lawrence Berkeley National Laboratory.
The researchers directly observed for the first time how metallic nanoparticles, used as catalysts in numerous industrial processes, activate catalytic processes. Using a light source one million times brighter than the sun, the researchers were able to observe chemical reactivity on single platinum particles similar to those used as industrial catalysts. What they found is that chemical reactivity primarily occurs on the particles’ periphery or edges, while lower reactivity occurs at the particles’ center.
The different reactivity observed at the center and edges of platinum particles corresponds to the different properties of the platinum atoms in the two locations. The atoms are mostly flat at the center, while they’re corrugated and less ordered at the edges. This disorderly or “defective” structure means that platinum atoms at the edges are not totally surrounded by other platinum atoms and will therefore form stronger interactions with reactant molecules. Stronger interactions can activate the reactant molecules and initiate a chemical reaction that will transform the reactant molecule into a desired product.
The research findings validate a wellknown hypothesis in the world of catalysis, which correlates high catalytic reactivity with high density of atomic defects.
To peer into individual nanoparticles, researchers focused a bright infrared beam generated in a synchrotron (advanced light) source on the Berkeley campus into a thin probe with an apex diameter of 20 nanometers. The probe acts as an antenna, localizes the infra-red light in a specific range, and by that provides the capabilities to identify molecules on the surface of the catalytic nanoparticles. By scanning the particles with the nanometric probe while it is being radiated by the infrared light, the researchers were able to identify the locations and conditions in which chemical reaction occurs on the surface of single particle.
Incorporating snow data collected from space into computer climate models can significantly improve seasonal temperature predictions, according to researchers at the University of Texas at Austin have found.
The findings, published recently in Geophysical Research Letters of the American Geophysical Union could improve decision- making months in the future to help farmers, water providers, power companies and others that benefit from the use of seasonal climate predictions. Snow influences the amount of heat that is absorbed by the ground and the amount of water available for evaporation into the atmosphere, which plays an important role in influencing regional climate.
“We’re interested in providing more accurate climate forecasts because the seasonal timescale is quite important for water resource management and people who are interested in the next season’s weather,” said Peirong Lin, the lead author of the study.
Seasonal forecasts are influenced by factors that are significantly more difficult to account for than the variables for daily to weekly weather forecasts or long-term climate change, said Prof. Zong-Liang Yang, a co-author of the study.
“Between the short and very long time scale, there’s a seasonal time scale that’s a very chaotic system,” Yang said. “But there is some evidence that slowly varying surface conditions, like snow cover, will have a signature in the seasonal timescale.”
The researchers found that incorporating snow data collected by NASA satellites into climate models improved regional temperature predictions by 5% to 25%. These findings are the first to go beyond general associations and break down how much snow can impact the temperature of a region months into the future. Improving temperature predictions is a key element to improving the computer models that provide climate predictions months in advance.
The researchers analyzed how data on snow cover and depth collected from two NASA satellites affected temperature predictions of the northern hemisphere in a climate model. The computer model’s temperature improvement changed depending on the region and time, with the biggest improvements happening in regions where ground-based measurements are sparse, such as Siberia and the Tibetan Plateau.
In the future, the researchers plan to expand their research to predict other climatic factors, such as snowfall and rainfall.
“Such use of satellite data will be standard,” said Koster. “Pioneering studies like this are absolutely critical to seeing this happen.”