It is not unusual for a consulting firm to coin a term to generate some buzz around a business practice on which its experts advise.

It’s sometimes as simple as turning an adjective into a noun, as McKinsey & Co. did with the word “digital” in a recent report on information technology in the chemical industry. It’s somewhat bold, however, when the word seems to describe a practice at which targeted clients have excelled for decades.

“There is a lot of excitement about the potential of digital,” McKinsey proclaims. It goes on to define digital as an “umbrella term for all the digital-related topics, including new or enhanced ways of operating businesses by using data, analytics, and new digitally enabled technologies, communications, and platforms.”

But hasn’t the chemical industry long been a digital leader, installing advanced financial management software and spending billions of dollars preparing for the shock of Y2K? Aren’t plants and laboratories today highly automated, filled with the latest computers? There wouldn’t appear to be much chance for IT excitement in chemicals.

Yet enthusiasm for digital as the “next big thing” is borne out in recent announcements by BASF, Dow Chemical, Evonik Industries, and others that describe partnerships with computer giants such as IBM and Hewlett Packard Enterprise (HPE). These new deals are touted as taking the computing-intensive components of science and business into a new realm that Evonik, for one, calls “digitalization.”

The announcements highlight investments in a new generation of high-powered supercomputers such as the HPE Apollo 6000 that BASF is installing as a digital processing center for its worldwide operations.

But the news also has to do with applications for that computing power. Firms are adopting artificial-intelligence- and machine-learning-enabled methods of computing that accelerate the speed and broaden the scope of experimentation by making use of the vast amounts of data now available in the lab and manufacturing plant.

With cloud computing making data storage and access an inexpensive commodity, the focus in IT development has shifted to crafting software that supports methods of extracting meaning from data generated in materials science R&D.

BASF says the Apollo 6000, to be installed at its headquarters in Ludwigshafen, Germany, will be one of the world’s largest supercomputers for industrial research.

“The new supercomputer will promote the application and development of complex modeling and simulation approaches, opening up completely new avenues for our research at BASF,” Martin Brudermüller, the chemical company’s chief technology officer, said at the time of the announcement.

The supercomputer will include Intel’s Xeon processors and other components to boost bandwidth. It will be deployed to answer complex questions and reduce the time required to obtain results from several months to days. At 1.75 petaflops, a unit of computing speed equal to 1,000 million million (10¹⁵) operations per second, the Apollo 6000 has 10 times the computing power currently dedicated to scientific computing at BASF and will rank as the 65th largest supercomputer in the world, according to the company.

Meanwhile, Evonik will work with IBM as part of its newly declared digitalization program, for which the German company says it is committing $120 million. The partnership is casting a wider net than BASF’s and is looking at bringing an elevated level of computing firepower to a broad range of business functions. It will incorporate cloud-based technologies, management of distributed device networks via the so-called internet of things, and blockchain, a digital ledger that records transactions between two parties through a peer-to-peer computer network.

Evonik will also tap into IBM’s new capabilities in quantum computing for R&D modeling. In a break from standard binary computing systems, quantum computing performs calculations using bits, or “qubits,” that can exist in a state of superpositioned zeros and ones. It is a methodology nearly catered to materials research in that it employs principles of physics developed in the study of molecular composition. Other companies, including Dow, are developing applications for quantum computing, prompted, according to some industry watchers, by the imminent debut of quantum computers from conventional hardware companies and Google.

But Dow’s new partnership is not with a computer company. Instead, the chemical maker has signed with a quantum computing software firm, 1QBit. Through the collaboration, Dow hopes to glean insight on how quantum computing methodologies can advance research efforts. 1QBit, meanwhile, seeks to use Dow’s experiment design expertise in developing software for materials science.

Similarly, Solvay is hoping to gain an inside track on next-generation computing by investing $2 million in MultiMechanics, a virtual testing software firm focused on modeling and failure prediction in materials research. Solvay says the software will advance its high-performance polymer and composites pipeline for auto and aerospace markets.

Going full digital

“We generally see digitalization bringing huge opportunities in value creation,” says Stephan Schenk, team leader for high-performance computing databases at BASF. “All the other companies are pushing for opportunities, too, which is why you are seeing a lot of stories.” But every industry—indeed every company—has its own take on what digitalization means, he says. “To us, it means the use of digital tools to boost our development process.”

Although BASF has decades of experience with high-powered computing, the partnership with HPE will significantly boost its activity. “It’s not new, really,” Schenk says, “but it’s the first time we’ve had this amount of computing capabilities.”

The partners will focus not only on increasing speed in R&D and commercialization but also on identifying areas in which advanced modeling and testing methodologies can break new ground in the lab.

“There are a lot of questions in our product development cycle that can be answered or augmented with information from simulation,” Schenk says. “You can narrow down the number of experiments you need to do to create a product. You can also gain more insight into how things work in reality.” The work will entail a new level of complexity in mathematical modeling, he points out. “You need more than a laptop.”

BASF chose HPE as a development partner, Schenk says, because of the power of the company’s latest technology and its service approach, which will configure the commercially available supercomputer to BASF-specific applications. BASF will turn to another partner, Intel, to optimize its programming code to work with the Apollo 6000.

In recent months, BASF has unleashed supercomputing on an agricultural chemical project, modeling a new functional polymer for the stable formulation of an unspecified active ingredient. From more than 10 million possibilities, the company says, researchers were able to work out the appropriate polymer structure. BASF also partnered with ZedX, a computer modeling firm, to develop a model that, based on weather and environmental conditions, identifies the right window of application for a BASF herbicide. BASF acquired ZedX earlier this year.

Leap forward

Other companies describe new projects building on a heritage of leadership in IT. “Anyone can tell you that Dow is a leader in supercomputing,” says A. N. Sreeram, the firm’s chief technology officer. “We built our own supercomputer eons ago.”

Since then, Dow has kept up with technology in partnerships with universities and national labs. Now supercomputers are “almost commoditized,” he says. Looking forward, Dow is interested in exploring software applications for quantum computing—thus the partnership with 1QBit.

“Long-term competitive advantage will come through a combination of proprietary data and the software used to extract that data,” says Keith Watson, vice president of core research at the company.

Dow is not in the business of building computers, he points out, and all the hardware the company requires is commercially available. Dow’s focus now is on developing software that will allow it to take advantage of a new generation of hardware, especially in quantum computing, and tailoring it to Dow’s needs in the lab.

Evonik says it signed up IBM as the technology partner for its digitalization program based on IBM’s strength in computer technology, especially its Watson supercomputers. “We want to use these internally and externally,” says Henrik Hahn, Evonik’s chief digital officer. “For example, the Watson system can help us get faster relevant findings in the research and development area. We can also more effectively address customer-applied, technology-related questions.”

The first project with IBM will be to establish what Evonik is calling a digital “knowledge corpus” composed of both in-house data and know-how as well as publicly available information. Watson will provide a cognitive search and analysis function and a way to identify connections in data sets.

Evonik partners with universities, such as the University of Duisburg-Essen, and government labs. Hahn notes, however, that solutions to specific problems in physics, chemistry, and materials research are outside the reach of classical personal computers and supercomputers used in most universities and government facilities. These challenges point toward the development of quantum computing.

“Evonik will be granted access to the quantum computing initiative of IBM, which has recently introduced a prototype of a quantum computer for commercial use,” Hahn says.

Joachim Schmider, an IBM associate partner for digital strategy in Germany, Switzerland, and Austria, says Evonik will access IBM’s Watson Explorer and Watson Knowledge Studio systems. Explorer, he says, is IBM’s cognitive search and content analysis platform. Cloud-based Knowledge Studio enables developers to identify unstructured data that can be analyzed by Explorer.

The partnership will encompass a range of new computing techniques in development at IBM, including cognitive and cloud-based data analysis platforms, blockchain, and smart device networking.

“I see big changes in the game when it comes to how to leverage new technologies such as the cloud in new ways, combining data not combined in the past, getting meaning out of it, and doing something with it,” Schmider says. “But it’s not just about data and technology. It is especially about business models, service solutions for customers, and training qualified staff.”

Software frontiers

As technology giants line up to debut a new generation of quantum computing hardware, software companies launched in the past five years are exploring applications for specific industries, including chemicals and materials.

1QBit, formed in 2012, is “engaging with customers to help them shape the hardware to achieve their goals,” says Andrew Fursman, the firm’s chief executive officer.

Although 1QBit is working with multiple industries, chemicals and materials science are a primary field of endeavor. “There is a strong understanding in the quantum computing community that their first real applications would be in quantum chemical and molecular simulation,” Fursman says.

The original motivation of quantum theorists, he notes, was to simulate molecules more accurately. While conventional computers have managed rough approximations, researchers at companies like Dow want to glean greater insights from huge stores of molecular data via the principles of quantum computing. They are interested in exploring applications that will cater emerging hardware systems to their specific needs.

“We are looking at the problems people are trying to solve and working our way back,” Fursman says. Advanced software should allow customers to narrow down the hardware selection from all the choices available. “We like the idea of being hardware agnostic,” he says.

Fursman emphasizes that quantum computing will not gain traction at the expense of classical supercomputing applications. “We see classical computers and quantum computing working hand in hand and well together,” he says. “We don’t think quantum computing will mean having to throw away your laptops.”

Working with big data

Dayton Horvath, an industry analyst who has reported on digitalization for Lux Research, sees ample hype in current discussions of IT in the chemicals sector. But it is clear that methodologies old and new—including artificial intelligence and machine learning—are coalescing around the problems posed by “big data.” Digital systems that can manage huge data sets are important because they can increase efficiency and innovation in R&D, he says.

“Digital technology allows you to look at factors you wouldn’t otherwise be able to see in a traditionally very slow and unsure R&D process,” Horvath says. “You can make a small investment and remove human bias and accelerate the R&D timeline by looking into places you didn’t think of.”

Researchers are better able to model specifications such as human toxicity, corrosion resistance, and color with artificial intelligence and machine learning supplementing traditional physics-based modeling and simulation.

“Having something like machine learning allows you to look at all these data and turn over more rocks,” he explains. “It doesn’t look at things from an equation-based perspective.” Data supplemental to basic experimental parameters allow researchers to select and ultimately process materials with information about properties and applications that they otherwise wouldn’t have.

While the major IT vendors are lining up with powerful computing architectures, Horvath says software start-ups are focusing on the needs of the materials science sector and developing software-as-a-service products to put the new IT systems to work in materials R&D. “The news in this area is around the start-ups providing services around machine learning,” he says.

Citrine Informatics, which launched in 2013, is among the firms offering advanced computing applications such as artificial intelligence and machine learning for materials science research as web-based software or software as a service.

“By and large, artificial intelligence as we think of it today—being able to analyze very large-scale systematic data and find trends too complicated for humans to see and finding automated ways to extract insights—has not been used by materials companies,” says CEO Greg Mulholland.

But Citrine’s founders saw that the industry was changing. The desire for speed and innovation in the laboratory was joining traditional business considerations of cost and efficiency. The rise of advanced materials divisions such as the one created in the Dow-DuPont merger also pointed to a new focus on materials.

And materials science is a fertile area for software development, Mulholland says, given the close alignment between tenets of quantum chemistry and the logic of emerging IT disciplines such as machine learning. Chemistry also creates an engine for machine learning with its principle of developing models for simulation using incoming data.

“We use internal mechanisms of artificial intelligence and inject chemical theory,” Mulholland says in describing software development at Citrine. “We give the AI system an undergraduate degree in chemistry, and it earns a Ph.D. from the data it is exposed to.”

The result is a collapsing of the iterative process of experimentation. “It isn’t a magical one-time tool but a system that learns along with you,” Mulholland explains. In doing so, a digital experimentation technique can result in a 50–70% reduction in time and cost from first specifying materials to eventually creating a new chemical or other product, he says.

Although IT activity in the chemical industry has reached a new level, Mulholland and others recognize an element of public relations in the recent announcements. The major companies are eager to be seen as adopting next-generation computing by their customers, employees, and investors, he says. “It’s telling that a stalwart like Dow wants to tout its partnership [with 1QBit].”

Fursman at 1QBit says the current rush to lay out IT strategies in press releases and at press conferences is also influenced by an environment in which IBM’s Watson supercomputers and HPE show up in television commercials. McKinsey is right that “digital” is generating a lot of excitement, and the chemical majors may indeed want to be seen as part of the action.

The announcements also indicate that the materials industry is confident about its foray into next-generation computing.

“The prevailing wisdom,” Fursman says, “has shifted from ‘this stuff may someday be possible’ to ‘now this is pretty inevitable.’ ”