2026-08-08 02:00:01
The transition from a purely technical expert or individual contributor position to a broader leadership role is one of the most challenging phases in a STEM career. It requires moving away from relying solely on technical excellence toward mastering systems thinking, adaptive leadership, and team alignment.
To help mid-career professionals navigate the shift, the inaugural IEEE International Leadership Conference is designed to provide attendees with practical tools to step into broader responsibility and champion an entrepreneurial mindset.
The ILC event is scheduled for 3 and 4 October in Budapest. Registration is open.
To successfully step into a leadership role, technical professionals need to look beyond their individual output and focus on “understanding the larger system, and championing innovation by building trust and aligning new ideas with organizational goals,” says IEEE Life Senior Member Daniel Sniezek, cochair of the ILC program committee.
Because engineering decisions don’t exist in a vacuum, navigating the larger system requires recognizing how technical choices intersect with the organization’s broader business, operational, and ethical realities, Sniezek says.
By letting go of the need to be the sole technical expert and focusing instead on collaborative empowerment, he says, engineers can pivot into transformational leaders who align new initiatives with the organization’s strategic vision.
Ultimately, over the span of a career, an individual’s leadership journey evolves far beyond personal advancement to “creating a lasting legacy through the people you develop, the knowledge you share, and the innovations you inspire,” he says.
Championing disruptive ideas within established corporate structures—sometimes called the intrapreneur’s dilemma—does not mean working against the organization. Rather, it requires emerging leaders to act like business owners instead of passive task-takers.
To begin thinking like an entrepreneur from within, professionals should shift their focus from merely executing assigned work to proactively identifying hidden areas that would create value for the company, building trust with colleagues, and presenting bold innovations as solutions to the organization’s long-term strategic goals.
That kind of self-starting entrepreneurial mindset is how leaders create opportunities out of institutional constraints.
IEEE Senior Member Deyasini Majumdar, cochair of the ILC program committee, advises professionals to exercise leadership and strategic thinking skills without being asked.
“Within the constraints of established organizational structures you can unearth a treasure trove of opportunities to innovate,” Majumdar says. “Remember: A key trait of an effective leader is to engineer solutions and lead, even in the face of difficulties.”
Leadership is a multidirectional exchange of ideas across generations—which is one focus of the ILC.
Although emerging leaders can gain invaluable strategic guidance from seasoned executives, the relationship is a dynamic, two-way street.
Modern leadership requires established executives to remain active learners. Addressing what senior leaders can glean from their mid-career counterparts, Majumdar emphasizes, the leaders must maintain “the openness to seek opportunities, to quickly adapt, and to learn and grow with everyone around them.”
A continuous-learning mindset is what keeps leaders agile and effective in a rapidly changing technological landscape, he says.
The mutual openness can serve as a bridge between generations.
Whether an emerging professional is making a mid-career pivot from technical expert to manager, or a senior executive is transitioning into a mentoring and advisory role, the fundamental rule of transformational leadership is similar. Success means shifting your focus from individual achievement to enabling the capability, growth, and legacy of others.
To help with the shift toward transformational leadership, the ILC is featuring sessions focused on questions professionals must ask at key career inflection points.
Rather than a single workshop, the distributed sessions aim to address diverse professional transitions, such as evaluating promotions, learning how to influence laterally, pitching innovative projects, and sustaining leadership energy.
Inflection points include evaluating new internal roles; building lateral or upward trust; pitching an idea about a disruptive project; and facing rapidly expanding responsibilities.
The questions include:
The conference is designed to equip attendees with systems thinking and communication mastery needed to cultivate influence.
Leadership is not just about reaching the top; it is also about engaging in a collaborative effort to multiply your impact across the ecosystem.
2026-08-07 21:00:01
The history of networking is full of tools that repurposed solutions to very different kinds of problems first. Wi-Fi’s origins trace back, in part, to a team of Australian radio astronomers trying to detect signals from evaporating black holes. But the data-processing tools they’d developed also proved capable at extracting clean messages from any chaotic, echoing signal environment. Echoes are echoes, after all, whether from distant star systems or from the far corner of the house.
I research vehicle communications networks, connecting cars to cars and to transportation infrastructure like traffic lights—for tomorrow’s vehicle-to-everthing (V2X) networks.
V2X research has long relied on models that assume “perfect” or “ideal” network conditions, which is a simplifying assumption that makes the math tractable. But this assumption doesn’t reflect how real wireless signals behave in a moving, obstructed, high-density environment. That gap is exactly the kind of real-world unpredictability that open radio access networks (a.k.a. O-RAN)—an open, programmable architecture behind some 4G and 5G cellular networks—were built to manage.
So why has the O-RAN standard—which is open and available to be applied well beyond 5G telecom—never been used for vehicle communications?
Solutions to the vehicle-to-everything (V2X) problem have to date relied on new networking protocols built from scratch—only to discover chicken-and-egg problems, thorny standards wars, and real signal congestion challenges at scale.
By contrast, O-RAN allows V2X engineers to reuse the networking protocols already developed for cellular communications. O-RAN was developed assuming cellphone towers are generally fixed in place. But, as can be seen below, O-RAN accommodates mobile “towers”—cars and trucks, in this case—with little additional effort.
Self-driving vehicle technology has largely been an each-car-for-itself endeavor. Tesla’s approach, for instance, relies heavily on powerful on-board banks of computers and suites of sensors spread around the car.
However, as an alternative to the “data center on wheels” model, this new O-RAN approach to V2X relies on each car’s nearby neighbors, wherever they are on the road. Each O-RAN–connected vehicle can then use a diversity of cars’ sensors and viewing angles for better group coordination and decision-making.
There is, to be clear, no O-RAN V2X test network operating in the world. Not yet.
It was just 10 years ago that the Third-Generation Partnership Project (3GPP) released its initial cellular V2X standard. The 3GPP have refined V2X over three major releases since. In the U.S. and the EU, the FCC and related European agencies have put forward other standards for short-range wireless V2X communication protocols.
However, no consensus standard has yet emerged. So, lacking any clear, unambiguous guidance on the future of V2X networks, autonomous-car makers—like Waymo, Tesla, Zoox, and Cruise—have leaned more on self-reliance, bulking up each vehicle with as many sensors and GPUs as possible.
Here, though, is where O-RAN might be able to help.
A little like APIs (a.k.a. application program interfaces) connect one app to another on your smartphone, O-RAN serves as an API for the network itself. And because of O-RAN’s open standards, a wireless network becomes programmable, vendor-neutral, and open to custom applications called xApps.
To test our proof-of-concept framework, I have been part of a team simulating five minutes of O-RAN V2X network traffic over one square kilometer of urban area, using real buildings and real-world road layouts from OpenStreetMap and traffic patterns generated by the modeling package SUMO. The simulations assumed a traffic density of 50-70 vehicles per kilometer—not rush hour but not light traffic either. In our simulation, we assumed vehicles communicated via a millimeter-wave frequency of 28 gigahertz and that each component of our O-RAN V2X system had its own dedicated xApp.
Taken together, these inputs—real geometry, real traffic, and each vehicle’s live GPS position—constitute what network researchers call a digital twin of the urban environment. That’s a virtual replica detailed enough for the network to reason about the physical world in real time.
This virtual world gave us a real result, too.
The simulations, published recently in IEEE Network, revealed that existing V2X standards—in which cars uncoordinatedly spit out messages into the network—result in signals “talking” over each other some 80-100 percent of the time. However, using O-RAN signal coordination, the message “collision” rate dropped to near zero.
And that matters because a seized-up V2X network doesn’t just fail quietly. It can fail in ways that might make a road turn treacherous.
High-frequency data links between cars are already difficult to maintain, even on a clear day with no buildings or city infrastructure getting in the way.
Yet, in this situation, existing V2X networks leave a car to conduct blind searches for each dropped signal beam. Traveling at highway speeds, that search takes long enough for the surrounding world to change completely.
An O-RAN network continuously tracks signal conditions across the network, and in O-RAN V2X simulations, we also gave the network access to a detailed map of the urban environment—building positions, road geometry, intersection layouts—combined with each vehicle’s GPS trajectory. Together, these parameters let the network’s control layer predict where and when a signal link is about to fail and instruct each car’s antenna to adjust before the connection drops.
Signal pointing is one failure mode. Losing the connection entirely—because no direct path exists at all—is another.
Consider, for instance, a crossroads of two busy streets, with a few alleys and parking lots adding to the list of potential dangers.
If a signal from car A cannot reach car B directly, or if the path length is too far for an individual beam to travel, the signal must find an intermediary car or stationary sensor nearby that can pass along the message. And existing V2X standards are slow and reactive—polling potential relay vehicles one-by-one: Are you available? Can you redirect this message?
By contrast, O-RAN keeps a running graph of optimized message routes, accounting for a range of real-world constraints. So when an O-RAN link fails (whether that link is direct from sender to receiver—or indirect), the system already has a reroute mapped out.
This is partly why we included “multi-hop routing” in the O-RAN V2X simulations.
Multi-hop V2X O-RAN routing complicated three separate elements of the simulation: for each signal’s middleman (some cars may be ideally positioned to relay a signal from car A to car B, but we made the simulation neglect any cars that were also overwhelmed with their own signals and signal-processing needs); for each signal’s strength (we required that every intermediate link be able to maintain a stable network connection, factoring in distance and traffic conditions); and for each signal’s latency (we required a realistic accounting for added signal latency time for each additional hop in a multi-hop routing).
And with each added complication, O-RAN V2X multi-hop routing continued to extend the network’s capacity from 25 percent of nearby cars connected (without multi-hop) to nearly 100 percent (with multi-hop).
These complications, at least at the simulation level, did not slow down the V2X network.
We are in touch with potential collaborators and institutions to develop testbeds, prototype hardware, and tester vehicles for potential proving grounds. The Institute of Science Tokyo, for instance, has already expressed interest in working on some of these early-stage problems.
To date, our published research on O-RAN V2X has centered around a computer simulation only. Real-world hardware will undoubtedly surface challenges our simulation could not. So, questions of network latency and the computational overhead needed for O-RAN V2X signaling remain as yet unresolved.
Plus, concerns about full interoperability and realistic security will each demand their own investigations. After all, no one will trust a V2X network to do anything if that network’s cyber vulnerabilities haven’t been anticipated and patched in advance.
Realizing the O-RAN V2X vision will require progress on multiple fronts simultaneously. On the standards side, O-RAN’s vehicular extensions—the interfaces that allow vehicles to participate in the network as managed elements rather than passive users—would ultimately need to be formally adopted by the O-RAN Alliance and recognized by 3GPP’s V2X specifications. That process takes years.
On the industry side, there is a more immediate problem that our architecture is already positioned to solve: interoperability.
Today, a car made by one manufacturer cannot necessarily parse V2X sensor data sent from a car made by another. Firmware is proprietary; data formats differ. But an O-RAN control layer would act as a universal translator—normalizing each vehicle’s data into a common format and accelerating a push toward true multi-platform vehicle-to-vehicle communications. A more widespread and truly universal standard would, by itself, represent a substantial step forward for V2X.
2026-08-06 02:00:03
Today’s U.S. electrical grid, among the largest, most complex systems ever built, is operating at its limit. The combination of rapid industrial growth, more frequent extreme weather, and a record surge in electricity use has pushed the grid to its breaking point, according to the U.S. Department of Energy.
Built decades ago for a more predictable world in which power came mostly from centralized coal or gas plants and electricity use grew at a steady pace, the grid faces unanticipated strain due in part to growing demand from data centers. The jobs of professionals managing the infrastructure have evolved from traditional engineering tasks to complex, fast-moving challenges.
Industry reports show that millions of modern digital sensors, smart meters, and grid monitors are generating nonstop waves of information. The sheer volume of data requires instant, automated computer analysis because human operators cannot process it fast enough.
Pressure on utilities stems from two sources: a spike in electricity demand and a shift in how power is generated.
An example of the operational strain can be seen at the regional level. With the recent deployment of artificial intelligence tools and high-performance computing, data centers require immense amounts of energy to operate. The largest power transmission utility in Texas recently reported a staggering 220 gigawatts of new connection requests, driven largely by a surge in AI and cloud-computing facilities, according to a CNBC report.
Alongside the rise in regional demand, global energy networks are absorbing an unpredictable variety of weather-dependent renewable energy such as wind and solar. The switch creates a volatile operating environment wherein supply and demand are balanced, second by second, to prevent blackouts.
The challenges are compounded by the vulnerability of the grid’s physical and digital framework.
More-frequent severe weather events cause costly disruptions, such as the devastating winter freeze that crippled the Texas grid and record-breaking heat waves that have overloaded transformers.
Simultaneously, the energy networks’ digital architecture faces threats. As utilities replace outdated analog equipment with smart meters and control systems, they are increasingly vulnerable to cyberattacks.
To overcome physical and digital vulnerabilities, grid reliability organizations, such as those conducting North American security simulations like GridEx, emphasize that the grid must become smarter, more agile, and completely automated. Energy researchers are noting that the key to this change lies in integrating AI across every layer of utilities’ operations.
According to energy industry experts, using AI to manage power systems is no longer a futuristic research project; it has become a baseline operational necessity. Grid analysts emphasize that traditional grid-planning methods are too slow to handle rapid energy dynamics or to balance volatile renewable energy in real time within decentralized power systems such as microgrids.
AI can fill the gap by processing vast amounts of data instantly. Machine learning algorithms can quickly analyze information from thousands of sensors, historical usage patterns, and weather forecasts to predict issues before they happen.
An industrial digitization study conducted by McKinsey & Co. indicated that integrating advanced data and automation across infrastructure networks could reduce system design errors, decrease equipment downtime by up to 50 percent through predictive maintenance, and extend the lifespan of power machinery by up to 40 percent.
From forecasting energy spikes to automatically fixing localized voltage drops, AI acts as the digital backbone of a self-healing grid, experts say. Deploying the complex systems requires a new workforce: power engineers who understand data science, as well as data scientists who understand electricity.
To bridge the gap between groundbreaking AI research and practical field deployment, IEEE Educational Activities, in partnership with the IEEE Power & Energy Society, has launched the online Artificial Intelligence for Power and Energy Systems course program.
The program explores core challenges threatening modern utilities. Rather than treating AI as an unverified black box that operates without human supervision, the curriculum focuses on safety, asset preservation, and strict reliability standards.
The curriculum is designed to educate power system engineers, utility managers, and data scientists tasked with modernizing the grid. The program was developed by Fangxing “Fran” Li, professor of electrical engineering and computer science at the University of Tennessee in Knoxville and chair of the IEEE Working Group on Machine Learning for Power Systems.
The program breaks down the technical transition into five modules that bridge high-level theory with real-world solutions:
AI fundamentals. This module teaches engineers how basic machine learning models apply to power grids. It discusses how specialized neural networks solve complex power-flow calculations and how AI models can safely transition from computer simulations to physical, high-voltage equipment.
Accelerating grid control. Learners are taught to leverage deep reinforcement learning, an AI approach that uses trial and error, to accelerate automated grid adjustments during emergency power events.
Forecasting and data analytics. Using predictive modeling, engineers learn how to predict sudden demand surges, variable wind and solar outputs, and fluctuating wholesale electricity market prices to keep power affordable and available.
Physics-informed and safe AI. To address trust—a barrier to utility AI adoption—this course covers AI models hard-coded to obey the laws of physics. The approach is designed to ensure that automated algorithms never make erratic choices that damage grid equipment.
Generative AI and next-generation tech. Learners can explore the frontier of utility technology, including graph neural networks and large language models. This module highlights how generative AI can process complex, interdisciplinary data to streamline utility planning, emergency responses, and regulatory reporting.
The algorithmic literacy and practical execution tools provided by the course program can help convert systemic risks into grid resilience.
For individual access, visit the IEEE Learning Network. If you are looking for customized organizational options, contact a content specialist to discuss volume pricing.
2026-08-04 22:51:55
This report examines R&D waste and how AI adoption has outpaced the intelligence needed to make consequential decisions well.
What Attendees will Learn
2026-08-04 02:00:02
Most hospitals and health care providers use electronic health records instead of paper charts to note patient vaccinations, diagnoses, and procedures. AthenaOne, Epic, and Oracle Health are some of the systems employed around the world. Many patients can access their electronic medical records from home.
The platforms exist thanks to pioneering efforts such as the Medical Information System (MIS-I). The first hospital-wide computer system, it was developed in the 1960s by Lockheed Martin (then known as Lockheed Missiles and Space Co.) in partnership with El Camino Hospital, in Mountain View, Calif. Doctors and nurses used MIS-I (pronounced miss-ONE) to admit patients, order lab work and imaging, schedule follow-up appointments, and issue hospital bills, according to a 1973 article published by Datamation.
Although many people now know how to type on a keyboard, in the 1960s, most did not. Therefore, MIS-I included a light pen, which worked like a stylus for today’s touchscreens.
MIS-I was recognized as an IEEE Milestone during a ceremony on 14 May at El Camino Hospital. The IEEE Santa Clara Valley Section sponsored the Milestone.
“The medical information system was more than a technological breakthrough; it was proof of what can happen when clinicians, engineers, administrators, and community leaders unite around a common goal: improving care for patients,” Dan Woods said at the event. He is chief executive of El Camino Health, the nonprofit organization that maintains the hospital.
“This pioneering work helped establish the foundation for the modern medical informatics industry,” Woods said. “The legacy of Lockheed’s innovation continues to benefit patients and health care providers around the world, making this achievement truly worthy of lasting recognition.”
Prior to Lockheed’s effort, health records remained paper-based. They often were stored in dedicated rooms within the hospital. Files were kept in heavy-duty manila folders organized on mechanized open-shelf filing systems, revolving rotary files, or locked steel filing cabinets, according to EO Johnson Business Technologies. The process of retrieving a patient’s medical history was cumbersome and could hamper decision-making in a life-or-death situation. Paper records were prone to human error, according to an EHR in Practice article. In addition, upkeep could be costly due to administrative expenses such as transcribing doctors’ notes, storing patient charts, adding medical codes, and managing insurance claims.
Companies and universities including General Electric, IBM, and Harvard began exploring how to use computers to improve clinical care. They developed several systems for hospital laboratories to track test orders and results, as explained in the Milestone webpage.
In 1964 Lockheed was looking to diversify its portfolio, Melville Hodge, who helped lead the MIS development, said at the dedication ceremony. The company decided to apply its expertise to health care, and later that year this focus-area became part of a new information systems division. Hodge, who at the time oversaw multiple R&D efforts, became the driving force behind the MIS program.
MIS-I displayed patient information on a 14-inch television purchased from a department store. Below that monitor was a keyboard and a light pen.Ian Thomson/Computer History Museum
In 1966 Lockheed secured a contract with the Mayo Clinic, in Rochester, Minn., to assess its computer system needs and those of its two associated hospitals, Hodge wrote in a paper detailing MIS history.
He and a small team of engineers worked with Mayo Clinic physicians for two years to build the prototype of what would become MIS-I.
The system displayed patient information on a 14-inch television purchased from a department store. Below that monitor was a keyboard, and to its right was a printer. Doctors and nurses would swipe their ID badge to access the system, then use the keyboard to put information into the patient’s file or send a request to a pharmacy or laboratory. They also could print documents.
But one problem kept cropping up: Most doctors didn’t know how to type. The computer mouse was still in its infancy, and Hodge suspected it would not solve the problem, according to a video shown at the dedication ceremony. Instead, he “borrowed technology from a then-secret satellite program,” he said.
That technology was the light pen, which was used with MIT’s Whirlwind Computer in the 1950s.
“The insight that physicians could not and would not learn to type, combined with the innovative solution of light pen interaction, transformed an impossible dream into practical reality,” the Milestone proposers wrote.
To display text, the system used matrix programming, a 2D data structure consisting of rows and columns. Using the light pen, a doctor or nurse would select text from a list of general categories on the monitor. The options included the patient’s personal and medical information, family medical history, current illness, and physical exam findings, according to a 1968 article in the medical journal JAMA. The computer would display the requested information or list the next steps to complete tasks such as sending a prescription to a pharmacy. The keyboard remained part of the setup because it could allow users to input new information and update patient records.
To further develop the system, they submitted a proposal to the U.S. Department of Health, Education, and Welfare (now split into the Departments of Health and Human Services and Education) to secure additional funding, but it was rejected.
Herschel Brown, Lockheed’s executive vice president, and Kenneth Larkin, its director of information systems, decided to fund its commercial development, Hodge wrote.
When the company’s contract with the Mayo Clinic ended, the Lockheed team returned to Sunnyvale, California to refine, test, and deploy the system at El Camino Hospital.
“I admire Ed Hawkins, who was its first administrator, for having the courage to take on this kind of project while running a hospital that was only four years old at the time,” Hodge said at the dedication ceremony.
Starting in 1968, early prototypes were installed in the hospital’s M.D. lounges and nursing station at El Camino Hospital. The organizations worked to configure the system so it met the hospital’s needs.
By 1969, a number of monitors had been installed, including in admissions, pharmacy, and radiology. The information from all the connected machines was stored in a data center housed in a separate location outside the hospital.
In 1971 Lockheed encountered difficulties with its C-5A and L-1011 aircraft programs, according to Hodge. The company was forced to curtail discretionary new business programs including MIS-I. The program was sold to Technicon of Tarrytown, N.Y., a leader in clinical laboratory automation.
The medical information system business operated independently as a subsidiary unit, and the transition marked the beginning of MIS-I’s commercial expansion.
That same year, MIS-I went live for hospital-wide use. Physicians’ orders were communicated to other departments, test results and radiology reports were retrieved, and nursing care planning and documentation were available, according to the Journal of Nursing Scholarship. MIS-I supported most information handling for nurses, physicians, and other medical personnel in the hospital.
But the change was not welcomed by all, according to the video about the technology. Nurses tended to praise the system, but many doctors had a hard time transitioning from paper to computers. They complained they were “spending more time fighting a machine” than interacting with their patients, according to the video. Some even retired to avoid learning the system. But nurses fought to keep it, emphasizing to doctors how much it improved patient care.
In 1974 El Camino Hospital held a vote of medical staff to determine whether to keep the system or return to paper-based records. About 60 percent of doctors and more than 90 percent of nurses voted in favor of keeping it, according to the Milestone webpage.
“The medical information system was more than a technological breakthrough; it was proof of what can happen when clinicians, engineers, administrators, and community leaders unite around a common goal: improving care for patients.” —Dan Woods, El Camino Health CEO
In 1975 nonprofit Battelle of Columbus, Ohio, evaluated how well the system was working for El Camino Hospital. It found that MIS-I reduced the time nursing staff spent on clerical tasks, improved communications among departments, and facilitated better planning of patient care. The survey also showed that more readily available, complete, and accurate information was being used to administer care and monitor patient progress, according to the report.
By 1993, the technology was installed in more than 200 hospitals in the United States, Canada, and Europe, according to the Milestone entry.
El Camino Hospital used MIS-I for 34 years, until its decommissioning in 2005. It was initially replaced by Eclipsys Sunrise XA and then ultimately by Epic.
The dedication ceremony brought together IEEE leaders, hospital staff, and government representatives. Hodge and his family also attended. IEEE President-Elect Jill Gostin made a presentation about IEEE, and Brian Berg of the IEEE History Committee discussed the organization’s Milestone program.
Hodge participated in a Q&A session with Deb Muro, chief information officer of El Camino Health. He told a story about the early days of MIS-I that he said he will never forget. During a hospital board meeting at which physicians were complaining about the system, an announcement was made over the hospital’s public address system that MIS-I wasn’t working.
“I had to ignore it to survive,” Hodge said, laughing. “As physicians got more used to it, and with a phenomenal poking from the nurses, doctors who wouldn’t use it were forced to.”
A bronze plaque recognizing the MIS-I as an IEEE Milestone has been installed in the lobby of the hospital in Mountain View. The plaque reads:
From 1965 to 1974, the first hospital-wide computerized medical information system was created by Lockheed Missiles and Space Co. in partnership with El Camino Hospital. Innovative light-pen terminals enabled physicians and staff across all departments to efficiently and accurately access patient data and enter work orders. By providing immediate feedback and seamless communication, it reduced costs and errors, improved safety and outcomes, and led the way to modern medical and clinical informatics.
Reviewed by the IEEE History Committee and approved by the IEEE Board of Directors, IEEE Milestones recognize outstanding technical developments around the world that are at least 25 years old. The Milestone program is administered by the IEEE History and Heritage group.
To learn more about historical figures in engineering, IEEE Milestones, and IEEE History Center programs and events, check out The Institute’s IEEE Tech History collection. IEEE Spectrum also covers aspects of tech history.
2026-08-03 19:38:22
This article is brought to you by COMSOL.
In pursuit of improved range, greater reliability, and faster charging, electric vehicles are driving the demand for high-voltage electronics. Other applications driving this demand include wind farms, data centers, and server farms, to name a few. As the interest for high-voltage electronics increases, the risks associated with their sudden failure must be considered.
Much of what causes high-voltage equipment to malfunction can be linked to the conditions of the climate in which it operates. Specifically, condensation on electronic surfaces caused by humidity can lead to corrosion, which can result in stray leak current and dendrite shorting during Electrochemical Migration (ECM).
Predicting, mitigating, and helping proactively design to account for corrosion is the focus of the Centre for Electronic Corrosion (CELCORR) research group at the Technical University of Denmark (DTU). The group’s researchers are working with industry partners to develop models and simulation apps that will help in building robust electronics designs. Their goal is to develop knowledge that can be used for manufacturing electronics to withstand humid operating conditions.
Automotive electrification and renewable energy systems rely on electronics at all stages of the energy chain. When these electronics, such as the example PCB in Figure 1, are exposed to the effects of moisture, they can become potential failure points.
“Anywhere you are producing, converting, transporting, and using energy, you need these high-power electronic systems that get affected by the humidity,” explained Dr. Rajan Ambat, DTU professor and manager of CELCORR. Ambient moisture can seep into the devices and machines that require these electronics and cause unexpected functional issues through corrosion. When these electronics are involved in particularly high-voltage applications (such as wind farms, data centers, electric vehicles, and server farms), failure due to humidity exposure can even lead to fire.
“There might be a situation where somebody installs a solar panel near the seashore or in an area with high humidity, and within a short period of time, a conducive condition forms inside the electronics that results in a failure,” Ambat said. “This is why we need to understand exactly how the conducive condition of condensation is created, when the condition is created, and how the system is failing.”
Figure 1. The electrolyte potential and current density distributions on a PCB surface (with pinholes).CELCORR/DTU
Identifying corrosion as the underlying cause of some electronic failures is still a challenge. “Fifty percent of failures in electronics are currently branded with an unidentified root cause,” Ambat explained. “When engineers open up the system, they do not realize that the failure was due to corrosion, because moisture disappears without leaving any sign of corrosion unless there is ECM dendrite formation.”
This lack of awareness was a strong motivator for CELCORR, which turned to multiphysics simulation as a supplementary tool to help its partner organizations to better predict humidity-related issues at the design stage.
CELCORR believes the best way to identify and avoid electronic failures is to build more effective designs that better prevent corrosion from developing or can withstand a higher humidity load. Its research team applies its expertise in modeling to generate simulation apps that will help partner industries to evaluate safe designs for humidity robustness.
“We are at the intersection of materials science and the electronics industry. We work as a bridge between materials and electronics disciplines, using both kinds of language,” Dr. Anish Rao Lakkaraju, a postdoctoral researcher at CELCORR, explained.
To understand potential design issues, Ambat emphasized the importance of virtually breaking down systems to identify where problems may arise. “We need simulation software to analyze potential uses of designs and whether new designs are good or bad,” Ambat said.
Researchers at the Technical University of Denmark (DTU) are using simulation apps to predict corrosion and design electronics proactively to mitigate or withstand its effects.
Using the COMSOL Multiphysics software for investigation, the CELCORR research team together with other research partners (Aalborg University) built an example model with a simple PCB geometry that matched both its test circuit boards as well as the design of a device used by one of its partner companies. The team then added a water film layer on top to act as the relative humidity. From there, the team could introduce variation. “We change the layout, geometry, distance between electrodes, thickness of the water film, and conductivity of the water film depending on the conditions,” Ambat said.
Ambat and his team generate data on the effect of these variations and can identify which has the greatest impact on the device’s performance and whether any alterations can improve the device’s anticorrosion robustness. “We assume there is condensation forming on the electronic surfaces (Figure 2) and compute the electrochemical leak current for different design elements,” Ambat said. “The value of the computed electrochemical current between the parts will give us an indication of whether the PCB will be affected or not.”
Figure 2. A 10-µm water film condensation effect on an example PCB.CELCORR/DTU
Altering the design elements and solving the model equations again and again allows the team to better understand what makes a design effective. “Now, we are at the current form of the model, and we are quite happy with where the physics are at this point,” Lakkaraju said. This modeling, however, was just the first part of CELCORR’s overarching goal of illuminating the destructive potential of corrosion in electronics and the best ways to avoid it.
To open up and ease access to these models, CELCORR used the Application Builder in COMSOL Multiphysics to create simulation applications for the members of the industrial consortium. Built with a simple 3D circuit board geometry with two oppositely biased electrodes and a water layer to replicate corrosion-causing moisture, the apps provide a pared-back, straightforward interface where users can vary model inputs. “We focused on fundamental aspects,” Lakkaraju said. “We boiled down our partners’ overarching concerns to create two apps with very simple geometries and the simplistic stuff that can be varied over multiple parameters.”
The simple simulation apps shown in Figures 3 and 4 are designed to show companies how the distance between the electrodes and the thickness of the moisture layer affect the leak current through the water film depending on different parameters. By analyzing multiple design elements and parameters, users can determine the relative benefits of certain design elements on the humidity robustness. “The apps we have built have really helped because they give the electronics engineers a plug-and-play sort of approach,” Lakkaraju explained.
Figure 3. The UI of CELCORR’s standalone app showing the inputs that users can alter.CELCORR/DTU
“By using this app [Figure 3], companies have unlimited freedom to work with these sorts of variables,” Lakkaraju added. “This would be quite difficult to recreate in real life with physical design and testing, and the companies we work with are quite happy with the level of accuracy the app can provide.”
Figure 4. The UI of one of the simulation apps showing a streamline plot with inputs such as the cathode voltage and blockage length.CELCORR/DTU
Alongside its collaboration with the industry consortium, CELCORR is also working toward improving the world’s general understanding of corrosion’s impact on electronics. To do this, Ambat and his team are undertaking multiple projects, including actively adding greater complexity to their models. In a tertiary current distribution model they are building, the team is drilling down into each of the basic inputs used in a secondary current distribution model, zooming in to examine the effects of the set of even more detailed inputs each basic input comprises.
“The next point is to study what each of these detailed inputs does,” Lakkaraju said. In particular, the team is examining mass transport properties and the chemical reactions’ rate constants.
In addition to these ongoing studies, CELCORR is expanding the scope of its research to investigate corrosion in high-power, high-voltage systems. Thanks to a 2024 grant from the Grundfos Foundation, CELCORR was able to establish the Centre for Climate Robust Electronics Design (CRED). The center’s lab facilities and expertise are being developed to address the humidity-robustness requirements of today’s high-voltage and high-power electronic equipment. “Using CELCORR’s uniquely deep understanding of materials and corrosion, we are equipped to find the root cause and provide knowledge for environmentally robust designs,” said Ambat.
For all of its investigation, CELCORR continues to rely on the agility of the COMSOL Multiphysics software. As Lakkaraju explained, “It is really quite nice how a model can be adapted to a variety of combinations of materials, geometries, and parameters and how the software allows you to keep building on from there.”