The Jerusalem Post

First look inside nanoscale catalysts shows ‘defects’ are useful

- • By JUDY SIEGEL-ITZKOVICH

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.

SATELLITE SNOW DATA IMPROVES TEMP PREDICTION­S

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.”

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