In November 2013, an oil pipeline exploded in the Chinese city of Qingdao, killing 62 people and injuring 136. Eight months later, a similar explosion in Kaohsiung killed 32 people and injured 321.
The pipelines were made of steel of the same specification and failed after two decades of use in the same environment. The cause was corrosion – the degradation of a material by a chemical or electrochemical reaction with its environment.
Such disasters are common: every square kilometer of any Chinese city contains more than 30 kilometers of buried pipes, creating tangled networks of oil and gas lines, water mains, and electrical and telecommunications cables. Rust is also expensive.
According to a US survey, rust costs six cents for every dollar of GDP in the United States. Globally, this amount is more than US$4 trillion per year – the equivalent of 40 in damages from Hurricane Katrina. Half of that cost is in rust prevention and control, the other half in damage and lost productivity.
Lack of knowledge hinders our ability to prevent failures. Erosion of underground pipes is influenced, for example, by the composition, microstructure and design of materials, as well as by a raft of environmental conditions such as soil oxygen level, humidity, salinity, pH, temperature and biological organisms.
Many industries, including oil, gas, marine and nuclear, collect corrosion data to identify risks, predict the service life of components, and control corrosion. Most of this data is proprietary, and best practices are rarely shared. Oil spills, bridge collapses and other disasters keep on coming.
The demand for knowledge about corrosion is increasing with the increasing use of advanced materials in medical devices, biosensors, fuel cells, batteries, solar panels and microelectronics. Corrosion is the main restriction on many nanotechnology applications.
Efforts to make material data accessible, such as the Material Genome Initiative (MGI), focus on the ‘birth’ rather than the ‘death’ of the material. Online platform is desperately needed for Jung data sharing. Access to large amounts and different types of corrosion information, which researchers can investigate with data mining and modeling tools, will improve the forecast of corrosion failures and anticorrosion designs.
Complex processes
The biggest challenge in corrosion research is accurately predicting how a material will corrode in a given environment. This requires a thorough knowledge of all relevant factors and their interactions.
Yet precise models for the mechanism are lacking. It is impossible to forecast problems without historical data about material failures under various circumstances. And field performance cannot be assessed in laboratories when environmental parameters are unknown.
Corrosion data is hard to collect. Damage can take years or even decades to accumulate and any project tracks only a few contributing factors. Data sets need to be combined.
For example, early studies of marine erosion (for example, occurring at oil-drilling platforms) were unreliable because they considered only physicochemical processes (including pH, dissolved oxygen, and temperature), not seawater. on the effects of living organisms. The model has now been improved by the inclusion of genomic data.
Corrosion depends on local conditions. Steel structures that last for decades in arid parts of inland China fail within months in the moist and salty coastal regions of Southeast Asia.
Protective polymer coatings that have worked for years at northern latitudes can wear down in weeks near the equator, where higher doses of heat and ultraviolet radiation break chemical bonds more quickly.
Referring to common corrosion knowledge – such as how particular steels are affected by moisture, salt or air pollution – requires a combination of studies from many diverse environments. For example, a worldwide survey of weathering steel reviewed 22 years of exposure test results from 108 sites in 22 countries.
With the increase in global trade, the oil and gas, construction, car, electronics and other industries have called for the sharing of corrosion data between countries to ensure the quality and safety of their products. Millions of cars around the world have been recalled over the years due to unforeseen corrosion problems arising in destination countries.
China’s 2013 ‘Belt and Road’ initiative, which promotes industrial ties with countries along the Silk Road economic belt between China and the West, poses unprecedented challenges.
Rapid corrosion assessment, material selection and design will be required as billions of dollars in construction, transportation, energy and telecommunications projects begin in Asia, Africa and Europe.
Advanced materials introduce entirely new corrosion problems. For example, the electrochemical stability of noble metals such as platinum and gold rapidly declines as their dimensions are reduced to the nanometer scale.
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