“We have new requirements, new demands – for electric vehicles, in sustainability, also new methods like machine learning and” related technologies and approaches for researching tribology and developing lubricants, Liang told Lube Report during an interview here at the society’s annual meeting and exhibition.

“So there are lots of new opportunities,” she continued, adding that today’s college students “think they see the opportunity. They also see the responsibility. I think we’re in a good time right now.”

Hong is a professor of mechanical engineering in Texas A&M’s College of Engineering, one of the United States’ leading collegiate programs for the study of tribology and lubrication engineering. STLE’s meeting and exhibition is the world’s largest annual gathering about research and developments in those fields. More than 1,400 people attended this year’s event, officials said.

Officials stated that the challenge of recruiting talent to the fields has not completely disappeared, and that the organization continues working with member companies to promote opportunities in the industry.

The STLE event includes a trade exhibition and presentations of more than 500 papers spread over four days. Many concerned the biggest trends rolling over the lubricant industry these days – electric vehicles, sustainability and the uptake of technologies such as big data and machine learning, aimed at boosting the industry’s ability to develop solutions.

As electric vehicle sales continue their rapid growth, the lubricant industry is racing to develop several new products for them, including lubricants that can tolerate the high electrical currents in EVs and coolants to manage the large amounts of heat generated by EV batteries. Liang said progress is still needed for both categories – in lubricants to help the vehicles run more efficiently and it coolants to prevent fires.

As usual, this year’s meeting and exhibition spotlighted dozens of new products being introduced by suppliers of lubricants as well as lubricant additives, base stocks, equipment used for product testing and other ancillary products. The majority were pitched with some form of sustainability angle, many as reducing carbon footprints or improving fuel economy. Liang said much time and effort is being invested toward those ends and that it will continue for years.

There is widespread belief that big data and machine learning can help meet the demand for new products, Liang said. She added that they are starting to yield some fruit but that the full impact on this industry will not be realized for some years.