University of Houston professor Xiaonan Shan and the rest of his research team are celebrating fresh funding from a federal grant. Photo via UH.edu

A team of scientists from the University of Houston, in collaboration with Howard University in Washington D.C., has received a $1 million award from the National Science Foundation for a project that aims to automate the discovery of new clean-energy catalysts.

The project, dubbed "Multidisciplinary High-Performance Computing and Artificial Intelligence Enabled Catalyst Design for Micro-Plasma Technologies in Clean Energy Transition," aims to use machine learning and AI to improve the efficiency of catalysts in hydrogen generation, carbon capture and energy storage, according to UH.

“This research directly contributes to these global challenges,” Jiefu Chen, the principal investigator of the project and associate professor of electrical and computer engineering, said in a statement. “This interdisciplinary effort ensures comprehensive and innovative solutions to complex problems.”

Chen is joined by Lars Grabow, professor of chemical and biomolecular engineering; Xiaonan Shan, associate professor of electrical and computing engineering; and Xuquing Wu, associate professor of information science technology. Su Yan, an associate professor of electrical engineering and computer science at Howard University, is collaborating on the project.

The University of Houston team: Xiaonan Shan, associate professor electrical and computing engineering, Jiefu Chen, associate professor of electrical and computer engineering, Lars Grabow, professor of chemical and biomolecular engineering, and Xuquing Wu, associate professor of information science technology. Photo via UH.edu

The team will create a robotic synthesis and testing facility that will automate the experimental testing and verification process of the catalyst design process, which traditionally is slow-going. It will implement AI and advanced, unsupervised machine learning techniques, and have a special focus on plasma reactions.

The project has four main focuses, according to UH.

  1. Using machine learning to discover materials for plasma-assisted catalytic reactions
  2. Developing a model to simulate complex interactions to better understand microwave-plasma-assisted heating
  3. Designing catalysts supports for efficient microwave-assisted reactions
  4. Developing a bench scale reactor to demonstrate the efficiency of the catalysts support system

Additionally, the team will put the funding toward the development of a multidisciplinary research and education program that will train students on using machine learning for topics like computational catalysis, applied electromagnetics and material synthesis. The team is also looking to partner with industry on related projects.

“This project will help create a knowledgeable and skilled workforce capable of addressing critical challenges in the clean energy transition,” Grabow added in a statement. “Moreover, this interdisciplinary project is going to be transformative in that it advances insights and knowledge that will lead to tangible economic impact in the not-too-far future.”

This spring, UH launched a new micro-credential course focused on other applications for AI and robotics in the energy industry.

Around the same time, Microsoft's famous renowned co-founder Bill Gates spoke at CERAWeek to a standing-room-only crowd on the future of the industry. Also founder of Breakthrough Energy, Gates addressed the topic of AI.

ExxonMobil and Intel are working to design, test, research and develop new liquid cooling technologies to optimize data center performance and help customers meet their sustainability goals. Photo via Getty Images

ExxonMobil, Intel eye sustainable solutions within data center innovation

the view from heti

Two multinational corporations have announced a new collaboration to create energy-efficient and sustainable solutions for data centers as the market experiences significant growth.

ExxonMobil and Intel are working to design, test, research and develop new liquid cooling technologies to optimize data center performance and help customers meet their sustainability goals. Liquid cooling solutions serve as an alternative to traditional air-cooling methods in data centers.

“Our partnership with ExxonMobil to co-develop turnkey solutions for liquid cooling will enable significant energy and water savings for data center and network deployments,” said Jen Huffstetler, Chief Product Sustainability Officer, Intel.

According to consulting firm McKinsey, “a hyperscaler’s data center can use as much power as 80,000 households do,” and that demand is expected to keep surging. Power consumption by the U.S. data center market is forecasted “to reach 35 gigawatts (GW) by 2030, up from 17 GW in 2022,” according to a McKinsey analysis. Artificial intelligence and machine learning, and other advanced computing techniques are increasing computational workloads, and in return, increasing electricity demand. Therefore, companies are searching for solutions to support this growth.

ExxonMobil launched its full portfolio of data center immersion fluid products last year. The partnership with Intel will allow them to further advance their efforts in this market.

“By integrating ExxonMobil’s proven expertise in liquid cooling technologies with Intel’s long legacy of industry leadership in world-changing computing technologies, together we will further the industry’s adoption and acceptance as it transitions to liquid cooling technologies,” said Sarah Horne, Vice President, ExxonMobil.

Learn more about this collaboration here.

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This article originally ran on the Greater Houston Partnership's Houston Energy Transition Initiative blog. HETI exists to support Houston's future as an energy leader. For more information about the Houston Energy Transition Initiative, EnergyCapitalHTX's presenting sponsor, visit htxenergytransition.org.

The UH team is developing ways to use machine learning to ensure that power systems can continue to run efficiently when pulling their energy from wind and solar sources. Photo via Getty Images

Houston researcher wins competitive NSF award for work tying machine learning to the power grid

grant funding

An associate professor at the University of Houston received the highly competitive National Science Foundation CAREER Award earlier this month for a proposal focused on integrating renewable resources to improve power grids.

The award grants more than $500,000 to Xingpeng Li, assistant professor of electrical and computer engineering and leader of the Renewable Power Grid Lab at UH, to continue his work on developing ways to use machine learning to ensure that power systems can continue to run efficiently when pulling their energy from wind and solar sources, according to a statement from UH. This work has applications in the events of large disturbances to the grid.

Li explains that currently, power grids run off of converted, stored kinetic energy during grid disturbances.

"For example, when the grid experiences sudden large generation losses or increased electrical loads, the stored kinetic energy immediately converted to electrical energy and addressed the temporary shortfall in generation,” Li said in a statement. “However, as the proportion of wind and solar power increases in the grid, we want to maximize their use since their marginal costs are zero and they provide clean energy. Since we reduce the use of those traditional generators, we also reduce the power system inertia (or stored kinetic energy) substantially.”

Li plans to use machine learning to create more streamlined models that can be implemented into day-ahead scheduling applications that grid operators currently use.

“With the proposed new modeling and computational approaches, we can better manage grids and ensure it can supply continuous quality power to all the consumers," he said.

In addition to supporting Li's research and model creations, the funds will also go toward Li and his team's creation of a free, open-source tool for students from kindergarten up through their graduate studies. They are also developing an “Applied Machine Learning in Power Systems” course. Li says the course will help meet workforce needs.

The CAREER Award recognizes early-career faculty members who “have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization,” according to the NSF. It's given to about 500 researchers each year.

Earlier this year, Rice assistant professor Amanda Marciel was also granted an NSF CAREER Award to continue her research in designing branch elastomers that return to their original shape after being stretched. The research has applications in stretchable electronics and biomimetic tissues.
The new course will provide participants with insights on how to use robotics to enhance efficiency in data collection, AI data analysis tools for industry, risk management with AI, and more. Photo courtesy of UH

Houston university launches latest micro-credential course focused on AI, robotics for the energy industry

coming soon

The University of Houston will launch its latest micro-credential course next month that focuses on how AI and robotics can be used in inspection processes for the energy industry.

Running from March 22 through April 22, the course is open to "engineers, technicians and industry professionals with advanced knowledge in the dynamic fields of robotics and AI," according to a statement from UH. It will combine weekly online lectures and in-person hands-on demonstrations and provide participants with insights on how to use robotics to enhance efficiency in data collection, AI data analysis tools for industry, risk management with AI, and more.

“By blending theoretical knowledge with practical applications and hands-on experience, the course aims to empower participants with the skills needed to evaluate and adopt these advanced technologies to address real-world challenges in asset management,” Vedhus Hoskere, assistant professor at the UH Cullen College of Engineering, said in a statement. “We hope that upskilling and knowledge gained from this course will help accelerate the adoption of AI and robotics and contribute to the advancement of safer and more resource-efficient energy infrastructure systems.”

Hoskere will teach the course module titled “Computer Vision and Deep Learning for Inspections.” He also recently received a $500,000 grant from the Texas Department of Transportation (TxDOT) to look at how to use drones, cameras, sensors and AI to support Texas' bridge maintenance programs.

Other leaders of the UH Energy course will include:

  • Kimberley Hayes, founder of Valkim Technologies: Lead speaker who will provide an overview and introduction of AI applications, standards and certification
  • Gangbing Song, Moores Professor of Mechanical Engineering at UH: Machine learning hands-on exercises
  • Pete Peterson, head of product management and marketing with XaaS Lab: Computer vision technology in the oil and gas industry
  • Matthew Alberts, head of project management with Future Technologies Venture Venture LLC: Use cases, workflow and optimizing inspections with AI and drones
  • Suchet Bargoti, chief technology officer at Abyss Solutions: AI and robots for integrity management.

Registration accepted up to the first day of the course and can be completed online.

The world can't keep on with what it's doing and expect to reach its goals when it comes to climate change. Radical innovations are needed at this point, writes Scott Nyquist. Photo via Getty Images

Only radical innovation can get the world to its climate goals, says this Houston expert

guest column

Almost 3 years ago, McKinsey published a report arguing that limiting global temperature rises to 1.5 degrees Celsius above pre-industrial levels was “technically achievable,” but that the “math is daunting.” Indeed, when the 1.5°C figure was agreed to at the 2015 Paris climate conference, the assumption was that emissions would peak before 2025, and then fall 43 percent by 2030.

Given that 2022 saw the highest emissions ever—36.8 gigatons—the math is now more daunting still: cuts would need to be greater, and faster, than envisioned in Paris. Perhaps that is why the Intergovernmental Panel on Climate Change (IPCC) noted March 20 (with “high confidence”) that it was “likely that warming will exceed 1.5°C during the 21st century.”

I agree with that gloomy assessment. Given the rate of progress so far, 1.5°C looks all but impossible. That puts me in the company of people like Bill Gates; the Economist; the Australian Academy of Science, and apparently many IPCC scientists. McKinsey has estimated that even if all countries deliver on their net zero commitments, temperatures will likely be 1.7°C higher in 2100.

In October, the UN Environment Program argued that there was “no credible pathway to 1.5°C in place” and called for “an urgent system-wide transformation” to change the trajectory. Among the changes it considers necessary: carbon taxes, land use reform, dietary changes in which individuals “consume food for environmental sustainability and carbon reduction,” investment of $4 trillion to $6 trillion a year; applying current technology to all new buildings; no new fossil fuel infrastructure. And so on.

Let’s assume that the UNEP is right. What are the chances of all this happening in the next few years? Or, indeed, any of it? President Obama’s former science adviser, Daniel Schrag, put it this way: “ Who believes that we can halve global emissions by 2030?... It’s so far from reality that it’s kind of absurd.”

Having a goal is useful, concentrating minds and organizing effort. And I think that has been the case with 1.5°C, or recent commitments to get to net zero. Targets create a sense of urgency that has led to real progress on decarbonization.

The 2020 McKinsey report set out how to get on the 1.5°C pathway, and was careful to note that this was not a description of probability or reality but “a picture of a world that could be.” Three years later, that “world that could be” looks even more remote.

Consider the United States, the world’s second-largest emitter. In 2021, 79 percent of primary energy demand (see chart) was met by fossil fuels, about the same as a decade before. Globally, the figures are similar, with renewables accounting for just 12.5 percent of consumption and low-emissions nuclear another 4 percent. Those numbers would have to basically reverse in the next decade or so to get on track. I don’t see how that can happen.

No alt text provided for this image

Credit: Energy Information Administration

But even if 1.5°C is improbable in the short term, that doesn’t mean that missing the target won’t have consequences. And it certainly doesn’t mean giving up on addressing climate change. And in fact, there are some positive trends. Many companies are developing comprehensive plans for achieving net-zero emissions and are making those plans part of their long-term strategy. Moreover, while global emissions grew 0.9 percent in 2022, that was much less than GDP growth (3.2 percent). It’s worth noting, too, that much of the increase came from switching from gas to coal in response to the Russian invasion of Ukraine; that is the kind of supply shock that can be reversed. The point is that growth and emissions no longer move in lockstep; rather the opposite. That is critical because poorer countries are never going to take serious climate action if they believe it threatens their future prosperity.

Another implication is that limiting emissions means addressing the use of fossil fuels. As noted, even with the substantial rise in the use of renewables, coal, gas, and oil are still the core of the global energy system. They cannot be wished away. Perhaps it is time to think differently—that is, making fossil fuels more emissions efficient, by using carbon capture or other technologies; cutting methane emissions; and electrifying oil and gas operations. This is not popular among many climate advocates, who would prefer to see fossil fuels “stay in the ground.” That just isn’t happening. The much likelier scenario is that they are gradually displaced. McKinsey projects peak oil demand later this decade, for example, and for gas, maybe sometime in the late 2030s. Even after the peak, though, oil and gas will still be important for decades.

Second, in the longer term, it may be possible to get back onto 1.5°C if, in addition to reducing emissions, we actually remove them from the atmosphere, in the form of “negative emissions,” such as direct air capture and bioenergy with carbon capture and storage in power and heavy industry. The IPCC itself assumed negative emissions would play a major role in reaching the 1.5°C target; in fact, because of cost and deployment problems, it’s been tiny.

Finally, as I have argued before, it’s hard to see how we limit warming even to 2°C without more nuclear power, which can provide low-emissions energy 24/7, and is the largest single source of such power right now.

None of these things is particularly popular; none get the publicity of things like a cool new electric truck or an offshore wind farm (of which two are operating now in the United States, generating enough power for about 20,000 homes; another 40 are in development). And we cannot assume fast development of offshore wind. NIMBY concerns have already derailed some high-profile projects, and are also emerging in regard to land-based wind farms.

Carbon capture, negative emissions, and nuclear will have to face NIMBY, too. But they all have the potential to move the needle on emissions. Think of the potential if fast-growing India and China, for example, were to develop an assembly line of small nuclear reactors. Of course, the economics have to make sense—something that is true for all climate-change technologies.

And as the UN points out, there needs to be progress on other issues, such as food, buildings, and finance. I don’t think we can assume that such progress will happen on a massive scale in the next few years; the actual record since Paris demonstrates the opposite. That is troubling: the IPCC notes that the risks of abrupt and damaging impacts, such as flooding and crop yields, rise “with every increment of global warming.” But it is the reality.

There is one way to get us to 1.5°C, although not in the Paris timeframe: a radical acceleration of innovation. The approaches being scaled now, such as wind, solar, and batteries, are the same ideas that were being discussed 30 years ago. We are benefiting from long-term, incremental improvements, not disruptive innovation. To move the ball down the field quickly, though, we need to complete a Hail Mary pass.

It’s a long shot. But we’re entering an era of accelerated innovation, driven by advanced computing, artificial intelligence, and machine learning that could narrow the odds. For example, could carbon nanotubes displace demand for high-emissions steel? Might it be possible to store carbon deep in the ocean? Could geo-engineering bend the curve?

I believe that, on the whole, the world is serious about climate change. I am certain that the energy transition is happening. But I don’t think we are anywhere near to being on track to hit the 1.5°C target. And I don’t see how doing more of the same will get us there.

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Scott Nyquist is a senior advisor at McKinsey & Company and vice chairman, Houston Energy Transition Initiative of the Greater Houston Partnership. The views expressed herein are Nyquist's own and not those of McKinsey & Company or of the Greater Houston Partnership. This article originally ran on LinkedIn.

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University of Houston collaborates with county on future-facing sustainability efforts

dream team

Researchers at the University of Houston are partnering with the Harris County Office of County Administration’s Sustainability Office, the Harris County Energy Management Team, and other county staff in an effort to develop a comprehensive baseline of energy use and energy-use intensity that will aim to reduce energy costs and emissions in county facilities.

Once fully established, the team will work on tracking progress and evaluating the effectiveness of energy-saving measures over time. They will begin to build the foundation for future programs aimed at maximizing savings, reducing energy consumption, and increasing the use of renewable energy sources in county operations.

Harris County energy managers, Glen Rhoden and Yas Ahmadi, will work with UH professionals, including:

  • Jian Shi, UH Cullen College of Engineering associate professor of engineering technology and electrical and computer engineering
  • Zhu Han, Moores professor of electrical and computer engineering
  • Xidan "Delia" Zhang, UH research intern

The group began collaborating a year ago, and analyzed energy consumption data from county facilities.They were able to successfully identify key summertime energy-saving opportunities and completed retro-commissioning of four county buildings. Those efforts saved over $230,000 annually in electricity costs.

“This project is a prime example of how impactful research at UH can be when applied to real-world challenges, delivering tangible benefits to both the environment and the communities we serve,” Shi says in a news release.

The team will plan to do additional building projects, which includes the development of solar energy and heat pump initiatives, building automation system upgrades, and LED lighting installations. The goal is to reduce electricity usage by at least 5 percent per year for county facilities by 2030 and cut greenhouse gas emissions by 50 percent over the next 5 years for county buildings.

“Addressing climate change and the energy transition requires a collaborative effort that is not only data-driven and action-oriented but also human-centric,” Shi adds. “It’s about more than just technology—it’s about improving the quality of life for Texans.”

Houston-based autonomous trucking tech co. raises $20M

fresh funding

A Houston-based autonomous vehicle technology company has raised early funding.

Bot Auto has announced the completion of its pre-series A funding round which was oversubscribed and raised $20 million. The round was led by investments from Brightway Future Capital, Cherubic Ventures, EnvisionX Capital, First Star Ventures, Linear Capital, M31 Capital, Taihill Venture, Uphonest Capital, and Welight Capital.

“As true believers in autonomous trucking, we're thankful for our investors' shared vision,” Xiaodi Hou, founder and CEO of Bot Auto, says in a news release. “Our strong commitment, combined with recent AI advancements and a sharpened focus on operational efficiency, has created a clear path to commercialization.”

The funds raised will be focused on developing the technology and will opt to avoid unnecessary hiring ahead of operational maturity, scaling the operational footprint prior to product readiness, over expansion and partnership debt. The company aims for a more sustainable and efficient future, and is hoping its engineers and AV executives help Bot Auto become an autonomous trucking game changer.

The Investment is expected to help expand Bot Auto's tech development in autonomous trucking that will focus on safety and operation efficiency.

“Our prospects for success have never been more promising,” Hou adds. “ We march forward, committed to bringing this transformative technology to humanity for a brighter future.”

Bot Auto’s vision aligns with the pioneering spirit of Houston’s legacy in space exploration, striving to achieve remarkable feats in technology and transportation. The company is dedicated to leveraging this investment to make significant strides in the US autonomous trucking industry, ultimately contributing to a more sustainable and efficient future.

———

This article originally ran on InnovationMap.

Texas-based Tesla posts first quarterly increase in deliveries, but shares slump

mixed feelings

Low interest financing, sweet lease deals, price cuts and free charging boosted Tesla’s global deliveries in the third quarter, the first increase this year for the electric vehicle maker.

The Austin, Texas, company said Wednesday that it delivered 462,890 vehicles from July through September, bolstered by loans as low as 1.99%, and $299 monthly leases on the Model 3, its least expensive vehicle. It delivered 435,059 vehicles during the same period last year.

The figures for July through September came in slightly higher than analyst estimates of 462,000 for the period, according to data provider FactSet.

However, shares of Tesla Inc. dropped sharply in morning trading, down nearly 4%.

The deliveries were “good and a step in the right direction,” wrote Dan Ives of Wedbush, but that there would be pressure on the company's stock because investors had been hoping for even better.

“Overall, this is a clear improvement from the first half and we believe getting in the range of 1.8 million for the year is still the key and important bogey,” Ives said.

Tesla has struggled much of the year to sell its aging model lineup as growth in electric vehicle sales in the U.S. and Europe slowed due to concerns with range, price and the ability to charge on trips.

Falling sales early in the year led to once-unheard of discounts for the automaker, cutting into its industry leading profit margins. Analysts estimated that Tesla’s average vehicle sales price was $42,500 for the third quarter, the lowest price in four years.

The sales decline likely will pull down third quarter earnings when they are announced on Oct. 23.

Tesla’s sales decline comes as competition is increasing from legacy and startup automakers, which are trying to nibble away at the company’s market share.

Nearly all of Tesla’s sales came from the smaller and less-expensive Models 3 and Y, with the company selling only 22,915 of its more expensive models that include X and S, as well as the new Cybertruck.

Wedbush analyst Dan Ives wrote in a note to investors Tuesday that third-quarter sales would bring a rebound as China sales continue to increase and price and demand stabilizes.” As China continues to heat up on the demand story for Tesla with favorable leasing/financing terms and pent-up demand in the region, we are confident that we will see a significant growth figure in the region,” he wrote.

Europe will continue to be slow with macroeconomic pressures, and U.S. demand should stabilize, Ives wrote.

But BNP Paribas Exane said in an investor note that long term expectations of the market are somewhat high for Tesla. The company said its sales estimates for 2026 and 2027 “remain 10% to 15% below the street, respectively.”

Tesla is scheduled to unveil a purpose built robotaxi at an event next week.