Houston researchers develop material to boost AI speed and cut energy use

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UH researchers have developed a thin film that could allow AI chips to run cooler and faster. Photo courtesy University of Houston.

A team of researchers at the University of Houston has developed an innovative thin-film material that they believe will make AI devices faster and more energy efficient.

AI data centers consume massive amounts of electricity and use large cooling systems to operate, adding a strain on overall energy consumption.

“AI has made our energy needs explode,” Alamgir Karim, Dow Chair and Welch Foundation Professor at the William A. Brookshire Department of Chemical and Biomolecular Engineering at UH, explained in a news release. “Many AI data centers employ vast cooling systems that consume large amounts of electricity to keep the thousands of servers with integrated circuit chips running optimally at low temperatures to maintain high data processing speed, have shorter response time and extend chip lifetime.”

In a report recently published in ACS Nano, Karim and a team of researchers introduced a specialized two-dimensional thin film dielectric, or electric insulator. The film, which does not store electricity, could be used to replace traditional, heat-generating components in integrated circuit chips, which are essential hardware powering AI.

The thinner film material aims to reduce the significant energy cost and heat produced by the high-performance computing necessary for AI.

Karim and his former doctoral student, Maninderjeet Singh, used Nobel prize-winning organic framework materials to develop the film. Singh, now a postdoctoral researcher at Columbia University, developed the materials during his doctoral training at UH, along with Devin Shaffer, a UH professor of civil engineering, and doctoral student Erin Schroeder.

Their study shows that dielectrics with high permittivity (high-k) store more electrical energy and dissipate more energy as heat than those with low-k materials. Karim focused on low-k materials made from light elements, like carbon, that would allow chips to run cooler and faster.

The team then created new materials with carbon and other light elements, forming covalently bonded sheetlike films with highly porous crystalline structures using a process known as synthetic interfacial polymerization. Then they studied their electronic properties and applications in devices.

According to the report, the film was suitable for high-voltage, high-power devices while maintaining thermal stability at elevated operating temperatures.

“These next-generation materials are expected to boost the performance of AI and conventional electronics devices significantly,” Singh added in the release.

By prioritizing the deployment of smart, energy-efficient technologies, we can ensure that Houston remains at the forefront of the global energy landscape, setting the standard for other cities to follow. Photo via Getty Images

HVAC innovation has a huge role to play in Houston amid energy transition

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As Houston, the energy capital of the world, navigates the global energy transition, the city is uniquely positioned to lead by example. This transition isn’t just about shifting from fossil fuels to renewable energy; it’s about creating an ecosystem where corporations, research institutions, startups, and investors collaborate to develop and implement innovative technologies.

One of the most promising areas for reducing energy consumption and minimizing environmental impact is in heating, ventilation, and air conditioning, or HVAC, systems.

Houston’s intense weather patterns demand efficient and adaptable climate control solutions. Traditional HVAC systems, while effective in maintaining indoor comfort, often operate on fixed settings that don’t account for real-time changes in occupancy or weather. This results in energy waste and increased utility costs — issues that can be mitigated by integrating artificial intelligence into HVAC systems.

AI-driven HVAC systems offer a dynamic approach to heating and cooling, learning from user preferences and environmental conditions to optimize performance. These systems use advanced algorithms to continuously adjust their operation, ensuring that energy is used only when and where it’s needed. This results in up to 30 percent greater energy efficiency compared to conventional systems, translating into significant savings for consumers and a reduction in overall energy demand.

For a city like Houston, where energy consumption is a critical concern, the widespread adoption of AI-integrated HVAC systems could have a substantial impact. By optimizing energy use in homes, offices, and industrial spaces, these systems help reduce the strain on the electrical grid, particularly during peak usage times. Additionally, they contribute to lowering greenhouse gas emissions, aligning with Houston’s broader sustainability goals.

The potential of AI in HVAC systems extends beyond efficiency and environmental benefits. These systems enhance the user experience by offering precise control over indoor climates, adapting to individual preferences, and responding to external conditions in real-time. This level of customization not only improves comfort but also supports a smarter, more sustainable approach to energy management.

Houston’s energy transition requires the collective efforts of all sectors. While large corporations and government entities play a significant role, the contributions of startups, research institutions, and energy service companies are equally important. These entities are at the forefront of developing technologies that address both the economic and environmental challenges of our time. Investors are increasingly recognizing the value of funding solutions that offer long-term sustainability alongside financial returns, further driving the adoption of innovative energy technologies.

The integration of AI into HVAC systems represents a crucial step forward in this journey. As Houston continues to evolve as a leader in energy innovation, embracing advanced technologies like AI-driven HVAC systems will be key to achieving a more sustainable and resilient energy future. These systems are not just a technological advancement—they are a strategic tool in the broader effort to reduce energy consumption, lower emissions, and create a healthier environment for all.

At the heart of Houston’s energy transition is the commitment to building a future that balances growth with sustainability. By prioritizing the deployment of smart, energy-efficient technologies, we can ensure that Houston remains at the forefront of the global energy landscape, setting the standard for other cities to follow. As we move forward, the integration of AI into our energy infrastructure, particularly in HVAC systems, will be instrumental in shaping a sustainable and prosperous future for Houston and beyond.

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Trevor Schick is the president of KOVA, a Texas company creating sustainable solutions in building development.

This article originally ran on EnergyCapital.
The four-year agreement will support the team’s ongoing work on removing PFAS from soil. Photo via Rice University

Houston chemist earns $12M grant to support innovative soil pollutant removal process

making moves

A Rice University chemist James Tour has secured a new $12 million cooperative agreement with the U.S. Army Engineer Research and Development Center on the team’s work to efficiently remove pollutants from soil.

The four-year agreement will support the team’s ongoing work on removing per- and polyfluoroalkyl substances (PFAS) from contaminated soil through its rapid electrothermal mineralization (REM) process, according to a statement from Rice.

Traditionally PFAS have been difficult to remove by conventional methods. However, Tour and the team of researchers have been developing this REM process, which heats contaminated soil to 1,000 C in seconds and converts it into nontoxic calcium fluoride efficiently while also preserving essential soil properties.

“This is a substantial improvement over previous methods, which often suffer from high energy and water consumption, limited efficiency and often require the soil to be removed,” Tour said in the statement.

The funding will help Tour and the team scale the innovative REM process to treat large volumes of soil. The team also plans to use the process to perform urban mining of electronic and industrial waste and further develop a “flash-within-flash” heating technology to synthesize materials in bulk, according to Rice.

“This research advances scientific understanding but also provides practical solutions to critical environmental challenges, promising a cleaner, safer world,” Christopher Griggs, a senior research physical scientist at the ERDC, said in the statement.

Also this month, Tour and his research team published a report in Nature Communications detailing another innovative heating technique that can remove purified active materials from lithium-ion battery waste, which can lead to a cleaner production of electric vehicles, according to Rice.

“With the surge in battery use, particularly in EVs, the need for developing sustainable recycling methods is pressing,” Tour said in a statement.

Similar to the REM process, this technique known as flash Joule heating (FJH) heats waste to 2,500 Kelvin within seconds, which allows for efficient purification through magnetic separation.

This research was also supported by the U.S. Army Corps of Engineers, as well as the Air Force Office of Scientific Research and Rice Academy Fellowship.

Last year, a fellow Rice research team earned a grant related to soil in the energy transition. Mark Torres, an assistant professor of Earth, environmental and planetary sciences; and Evan Ramos, a postdoctoral fellow in the Torres lab; were given a three-year grant from the Department of Energy to investigate the processes that allow soil to store roughly three times as much carbon as organic matter compared to Earth's atmosphere.

By analyzing samples from the East River Watershed, the team aims to understand if "Earth’s natural mechanisms of sequestering carbon to combat climate change," Torres said in a statement.

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 scores prestigious NSF award for machine learning, power grid tech

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.

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This article originally ran on EnergyCapital.

The research outfit says North America leads global AI growth in oil and gas, with Houston playing a pivotal role. Photo via Getty Images

Report: Houston rises as emerging hub for $6B global AI in oil and gas industry

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Houston is emerging as a hub for the development of artificial intelligence in the oil and gas industry — a global market projected to be worth nearly $6 billion by 2028.

This fresh insight comes from a report recently published by ResearchAndMarkets.com. The research outfit says North America leads global AI growth in oil and gas, with Houston playing a pivotal role.

“With AI-driven innovation at its core, the oil and gas industry is set to undergo a profound transformation, impacting everything from reservoir optimization to asset management and energy consumption strategies — setting a new standard for the future of the sector,” says ResearchAndMarkets.com.

The research company predicts the value of the AI sector in oil and gas will rise from an estimated $3.2 billion in 2023 and $3.62 billion in 2024 to $5.8 billion by 2028. The report divides AI into three categories: software, hardware, and hybrids.

As cited in the report, trends that are sparking the explosion of AI in oil and gas include:

  • Stepped-up use of data
  • Higher demand for energy efficiency and sustainability
  • Automation of repetitive tasks
  • Optimization of exploration and drilling
  • Enhancement of safety

“The oil and gas industry’s ongoing digitization is a significant driver behind … AI in the oil and gas market. Rapid adoption of AI technology among oilfield operators and service providers serves as a catalyst, fostering market growth,” says ResearchAndMarkets.com.

The report mentions the Open AI Energy Initiative as one of the drivers of increased adoption of AI in oil and gas. Baker Hughes, C3 AI, Microsoft, and Shell introduced the initiative in February 2021. The initiative enables energy operators, service providers, and vendors to create sharable AI technology for the oil and gas industry.

Baker Hughes and C3 AI jointly market AI offerings for the oil and gas industry.

Aside from Baker Hughes, Microsoft, and Shell, other companies with a significant Houston presence that are cited in the AI report include:

  • Accenture
  • BP
  • Emerson Electric
  • Google
  • Halliburton
  • Honeywell
  • Saudi Aramco
  • Schlumberger
  • TechnipFMC
  • Weatherford International
  • Wood

Major AI-related trends that the report envisions in the oil and gas sector include the:

  • Digital twins for asset modeling
  • Autonomous robotics
  • Advanced analytics for reservoir management
  • Cognitive computing for decision-making
  • Remote monitoring and control systems

“The digitization trend within the oil and gas sector significantly propels the AI in oil and gas market,” says the report.

The project will focus on testing 5G networks for software-centric architectures. Photo via Getty Images

Rice lands federal funding for new 5G testing framework

money moves

A team of Rice University engineers has secured a $1.9 million grant from the U.S. Department of Commerce’s National Telecommunications and Information Administration to develop a new way to test 5G networks.

The project will focus on testing 5G networks for software-centric architectures, according to a statement from Rice. The funds come from the NTIA's most recent round of grants, totaling about $80 million, as part of the $1.5 billion Public Wireless Supply Chain Innovation Fund. Other awards went to Virginia Tech, Northeastern University, DISH Wireless, and more.

The project at Rice will be led by Rahman Doost-Mohammady, an assistant research professor of electrical and computer engineering; and Ashutosh Sabharwal, the Ernest Dell Butcher Professor of Engineering and chair of the Department of Electrical and Computer Engineering. Santiago Segarra, assistant professor of electrical and computer engineering and an expert in machine learning for wireless network design, is also a co-principal investigator on this project.

"Current testing methodologies for wireless products have predominantly focused on the communication dimension, evaluating aspects such as load testing and channel emulation,” said Doost-Mohammady said in a statement. “But with the escalating trend toward software-based wireless products, it’s imperative that we take a more holistic approach to testing."

The new framework will be used to "assess the stability, interoperability, energy efficiency and communication performance of software-based machine learning-enabled 5G radio access networks (RANs)," according to Rice, known as ETHOS.

Once created, the team of researchers will use the framework for extensive testing using novel machine learning algorithms for 5G RAN with California-based NVIDIA's Aerial Research Cloud (ARC) platform. The team also plans to partner with other industry contacts in the future, according to Rice.

“The broader impacts of this project are far-reaching, with the potential to revolutionize software-based and machine learning-enabled wireless product testing by making it more comprehensive and responsive to the complexities of real-world network environments,” Sabharwal said in the statement. “By providing the industry with advanced tools to evaluate and ensure the stability, energy efficiency and throughput of their products, our research is poised to contribute to the successful deployment of 5G and beyond wireless networks.”

Late last year, the Houston location of Greentown Labs also landed funds from the Department of Commerce. The climatetech startup incubator was named to of the Economic Development Administration's 10th cohort of its Build to Scale program and will receive $400,000 with a $400,000 local match confirmed.

Houston-based nonprofit accelerator, BioWell, also received funding from the Build to Scale program.
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Houston unicorn closes $421M to fuel first phase of flagship energy project

Heating Up

Houston geothermal unicorn Fervo Energy has closed $421 million in non-recourse debt financing for the first phase of its flagship Cape Station project in Beaver County, Utah.

Fervo believes Cape Station can meet the needs of surging power demand from data centers, domestic manufacturing and an energy market aiming to use clean and reliable power. According to the company, Cape Station will begin delivering its first power to the grid this year and is expected to reach approximately 100 megwatts of operating capacity by early 2027. Fervo added that it plans to scale to 500 megawatts.

The $421 million financing package includes a $309 million construction-to-term loan, a $61 million tax credit bridge loan, and a $51 million letter of credit facility. The facilities will fund the remaining construction costs for the first phase of Cape Station, and will also support the project’s counterparty credit support requirements.

Coordinating lead arrangers include Barclays, BBVA, HSBC, MUFG, RBC and Société Générale, with additional participation from Bank of America, J.P. Morgan and Sumitomo Mitsui Trust Bank, Limited, New York Branch.

“As demand for firm, clean, affordable power accelerates, EGS (Enhanced Geothermal Systems) is set to become a core energy asset class for infrastructure lenders,” Sean Pollock, managing director, project Finance at RBC Capital Markets, said in a news release. “Fervo is pioneering this step change with Cape Station, a vital contribution to American energy security that RBC is proud to support.”

The oversubscribed financing marks Cape Station’s shift from early-stage and bridge funding to a long-term, non-recourse capital structure, according to the news release.

“Non-recourse financing has historically been considered out of reach for first-of-a-kind projects,” David Ulrey, CFO of Fervo Energy, said in a news release. “Cape Station disrupts that narrative. With proven oil and gas technology paired with AI-enabled drilling and exploration, robust commercial offtake, operational consistency, and an unrelenting focus on health and safety, we have shown that EGS is a highly bankable asset class.”

Fervo continues to be one of the top-funded startups in the Houston area. The company has raised about $1.5 billion prior to the latest $421 million. It also closed a $462 million Series E in December.

According to Axios Pro, Fervo filed for an IPO that would value the company between $2 billion and $3 billion in January.

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This article first appeared on EnergyCapitalHTX.com.

Houston food giant Sysco to acquire competitor in $29 billion deal

Mergers & Acquisitions

Sysco, the nation's largest food distributor, will acquire supplier Restaurant Depot in a deal worth more than $29 billion.

The acquisition would create a closer link between Sysco and its customers that right now turn to Restaurant Depot for supplies needed quickly in an industry segment known as “cash-and-carry wholesale.”

Sysco, based in Houston, serves more than 700,000 restaurants, hospitals, schools, and hotels, supplying them with everything from butter and eggs to napkins. Those goods are typically acquired ahead of time based on how much traffic that restaurants typically see.

Restaurant Depot offers memberships to mom-and-pop restaurants and other businesses, giving them access to warehouses stocked with supplies for when they run short of what they've purchased from suppliers like Sysco.

It is a fast growing and high-margin segment that will likely mean thousands of restaurants will rely increasingly on Sysco for day-to-day needs.

Restaurant Depot shareholders will receive $21.6 billion in cash and 91.5 million Sysco shares. Based on Sysco’s closing share price of $81.80 as of March 27, 2026, the deal has an enterprise value of about $29.1 billion.

Restaurant Depot was founded in Brooklyn in 1976. The family-run business then known as Jetro Restaurant Depot, has become the nation's largest cash-and-carry wholesaler.

The boards of both companies have approved the acquisition, but it would still need regulatory approval.

Shares of Sysco Corp. tumbled 13% Monday to $71.26, an initial decline some industry analysts expected given the cost of the deal.

Houston researcher builds radar to make self-driving cars safer

eyes on the road

A Rice University researcher is giving autonomous vehicles an “extra set of eyes.”

Current autonomous vehicles (AVs) can have an incomplete view of their surroundings, and challenges like pedestrian movement, low-light conditions and adverse weather only compound these visibility limitations.

Kun Woo Cho, a postdoctoral researcher in the lab of Rice professor of electrical and computer engineering Ashutosh Sabharwal, has developed EyeDAR to help address such issues and enhance the vehicles’ sensing accuracy. Her research was supported in part by the National Science Foundation.

The EyeDAR is an orange-sized, low-power, millimeter-wave radar that could be placed at streetlights and intersections. Its design was inspired by that of the human eye. Researchers envision that the low-cost sensors could help ensure that AVs always pick up on emergent obstacles, even when the vehicles are not within proper range for their onboard sensors and when visibility is limited.

“Current automotive sensor systems like cameras and lidar struggle with poor visibility such as you would encounter due to rain or fog or in low-lighting conditions,” Cho said in a news release. “Radar, on the other hand, operates reliably in all weather and lighting conditions and can even see through obstacles.”

Signals from a typical radar system scatter when they encounter an obstacle. Some of the signal is reflected back to the source, but most of it is often lost. In the case of AVs, this means that "pedestrians emerging from behind large vehicles, cars creeping forward at intersections or cyclists approaching at odd angles can easily go unnoticed," according to Rice.

EyeDAR, however, works to capture lost radar reflections, determine their direction and report them back to the AV in a sequence of 0s and 1s.

“Like blinking Morse code,” Cho added. “EyeDAR is a talking sensor⎯it is a first instance of integrating radar sensing and communication functionality in a single design.”

After testing, EyeDAR was able to resolve target directions 200 times faster than conventional radar designs.

While EyeDAR currently targets risks associated with AVs, particularly in high-traffic urban areas, researchers also believe the technology behind it could complement artificial intelligence efforts and be integrated into robots, drones and wearable platforms.

“EyeDAR is an example of what I like to call ‘analog computing,’” Cho added in the release. “Over the past two decades, people have been focusing on the digital and software side of computation, and the analog, hardware side has been lagging behind. I want to explore this overlooked analog design space.”

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