BYLINE: Ula Chrobak

Read this story in the SLAC News Center

Newswise — Researchers at the Department of Energy’s SLAC National Accelerator Laboratory and collaborating institutions recently built a generative AI model that can recreate molecular structures from the movement of the molecule’s ions after they are blasted apart by X-rays, a technique called Coulomb explosion imaging.

The research, published in Nature Communications, is an important step toward being able to take snapshots of molecules during chemical reactions – an advance that could have important impacts in medicine and industry. The machine learning model closely predicted the geometries of a range of different molecules made of less than ten atoms, paving the way for applying the technique to larger molecules. “We were pretty excited about this,” said Xiang Li, an associate scientist at SLAC’s Linac Coherent Light Source (LCLS) and lead author of the study. “It is the first AI model built for molecular structure reconstruction from Coulomb explosion imaging.”

A new way to see molecules

Currently, there are limited options available for imaging isolated gas phase molecules. With electron microscopy, for example, subjects must be fixed in place, making it impossible to image free-floating molecules. And for diffraction-based techniques to work, the sample of molecules needs to be dense enough to generate a strong signal in the detector. The resulting image is technically an average of many molecules, restricting researchers from studying details only visible when imaging isolated molecules.

In the paper, the researchers instead focused on Coulomb explosion imaging. In this technique, an X-ray pulse hits a single molecule in a vacuum chamber, ripping off the molecule’s electrons. This leaves behind positive ions that explosively repel away from each other and smash into a detector. The detector captures their momentum, which can be used to reconstruct the structure of the molecule. “This technique has the ability to isolate minor details that are chemically relevant,” said James Cryan, LCLS interim deputy director for science, research and development, associate professor of photon science at SLAC and coauthor of the paper.

But this reconstruction process has so far been largely infeasible due to computing constraints. After the X-ray pulse strips away electrons, the remaining ions do not explode apart instantly. During this brief delay, the atoms can shift slightly, making it difficult to reconstruct the original structure using Coulombs law for electrostatic forces. “It will not be accurate because a simple use of that law only works if the charge-up process is instantaneous,” explained Li.

Making things even messier, every additional atom in the molecule adds an exponential level of complexity. “It’s very challenging to work backwards to get the original structure,” said co-author Phay Ho, a physicist with DOE’s Argonne National Laboratory. “It’s kind of like breaking a glass and trying to put it back together from how the pieces flew apart. Many problems in modern physics and chemistry involve reconstructing hidden structures from indirect measurements. This work demonstrates how AI can help tackle such inverse problems.”

Machine learning for molecular structures

The research team set out to build a machine learning model that could overcome this computing constraint. They developed and trained the model at SLAC’s Shared Science Data Facility (S3DF). Generative AI models are well-suited for the task because they “think” differently than a standard computer simulation. Instead of working through a series of equations, they learn by finding patterns in training data. Then, they use those patterns to make statistical predictions. 

To gather training data, the team turned to a simulation built by Ho. The simulation analyzes molecular structures and calculates the momentum of their ions following a Coulomb explosion. After running for over a month, the computing-intensive simulation, using both quantum mechanics and classical physics equations, produced a dataset of 76,000 molecular samples.

Initially, the researchers trained the AI on this dataset alone, which is small by AI-training standards, and they found the model predicted inaccurate structures from explosion data. So, they re-did the training, adding in another dataset derived using only classical physics. The second set was less precise but about 100 times larger than the first one.

This two-step training was the trick for predicting precise structures.

The researchers tested the AI model by prompting it to predict molecular structures in a portion of the simulation data it had not seen in training. The model, which the team named MOLEXA (short for “molecular structure reconstruction from Coulomb explosion imaging”), took the ion momenta and calculated the most likely structures. “We found that this two-step training process suppressed the prediction error by a factor of two,” said Li.

The team then tested MOLEXA with experimental datasets recorded at the Small Quantum Systems (SQS) instrument of the European X-ray Free-Electron Laser facility (European XFEL) in Germany. The molecules they tested included water, tetrafluoromethane and ethanol. They entered the experimental ion momenta into the model, reconstructed the molecular structures, and then compared the reconstructions to known structures listed by the National Institute of Standards and Technology.

They found the predictions largely overlapped with the established structures. Overall, the bonds were in the right spots, with only slight variations in their angles. The errors in position were generally less than half the length of a typical chemical bond. “The model is actually, most of the time, doing better than that,” added Li. “It is only a starting point for future research, which will not only improve model accuracy but also extend its applicability to larger molecular systems.”

Expanding to larger molecules and chemical reactions

The paper is a major step in advancing Coulomb explosion imaging, which has long been limited by the challenge of reconstructing molecular structures from experimental measurements. In future work, the researchers plan to scale up the number of atoms the machine learning model can piece back together and apply the model to time-resolved experiments at the LCLS and European XFEL. That will help researchers to reconstruct snapshots of molecules in motion, creating flip-book-like molecular movies with insights into how chemical reactions unfold. It will also help with the interpretation of data collected at the high X-ray pulse rates delivered by SLAC’s superconducting X-ray laser, Cryan said.

The team is also now testing the model’s ability to reconstruct molecules from incomplete data. Much of the time, the detector misses an ion produced in the Coulomb explosion. Li wants to know, for example: Can the AI still reconstruct an ethanol molecule if one or more of its hydrogen ions are not registered in the detector?

If these challenges are resolved, the technique could become more applicable in biology and chemistry research. Proteins, for instance, can consist of thousands of atoms. “That’s really the goal,” said Li. “We will be able to study systems that are more biologically or industrially relevant.”

The team also included researchers from the Stanford PULSE Institute; Stanford University; Kansas State University; European XFEL, Germany; the Max Planck Institute for Nuclear Physics, Germany; Fritz Haber Institute, Germany; and Sorbonne University, France. Large parts of this work were funded by the Department of Energy’s Office of Science. LCLS is an Office of Science user facility.

About SLAC

SLAC National Accelerator Laboratory explores how the universe works at the biggest, smallest and fastest scales and invents powerful tools used by researchers around the globe. As world leaders in ultrafast science and bold explorers of the physics of the universe, we forge new ground in understanding our origins and building a healthier and more sustainable future. Our discovery and innovation help develop new materials and chemical processes and open unprecedented views of the cosmos and life’s most delicate machinery. Building on more than 60 years of visionary research, we help shape the future by advancing areas such as quantum technology, scientific computing and the development of next-generation accelerators.

SLAC is operated by Stanford University for the U.S. Department of Energy’s Office of Science. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time.

BYLINE: Ashleigh Papp

Newswise — Using a tool to solve a protein’s structure, for most researchers in the world of structural biology and computational chemistry, is not unlike using the Rosetta Stone to unlock the secrets of ancient Egyptian texts. Once a protein’s structure has been discovered, or defined, one can infer crucial information about its function or, in a diseased state, its dysfunction. While researchers have been pursuing the quest of solving protein structure for decades, advancing tools and computing technologies offer a new frontier for this work.

A collaborative study recently published in Nature Communications unveiled a new computing program that offers a faster and more accurate way to determine protein structure at a new level of precision. Researchers from the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), along with an international team of researchers, were a part of the effort. This tool, dubbed AI-enabled Quantum Refinement, or AQuaRef for short, uses quantum-mechanical calculations (QM) and artificial intelligence (AI) to predict the highly-accurate placement of atoms and electrons to determine a protein’s molecular structure.

This program is a part of Phenix, a comprehensive software suite that generates realistic computer models used by structural biologists around the world to solve macromolecular structures. “We’re all basically a bunch of proteins,” said Nigel Moriarty, a Berkeley Lab researcher and contributor to the recent publication. “They do so much in our bodies that detail the processes of life. Understanding their structure can give us insights into the mechanisms that cause disease in humans or produce energy in plants. All of this knowledge can lead to more effective therapeutics and bioenergy production.”

The current way of mapping a protein’s structure entails bringing together two streams of information: experimental data produced through techniques like X-ray crystallography and cryogenic electron microscopy (cryo-EM), and theoretical data that exists in a library of detailed, known protein structural information. But the current options are limited, explained Moriarty, a computational research scientist in the Molecular Biophysics and Integrated Bioimaging (MBIB) Division’s Phenix group. Our understanding today is limited to the chemical entities that have already been defined and doesn’t yet include meaningful noncovalent interactions, the type of attraction typically seen holding a protein in its structural form. “That’s where quantum and AI come in,” he said.

Nearly five years ago, members of the Phenix team began working with researchers at Carnegie Mellon University to explore how they might be able to apply their coding work to Phenix’s offerings. The collaborative approach, coupled with 15 years of incremental research, led to this breakthrough program. In addition to Moriarty, other members of the Phenix team involved in this work were Paul Adams and Billy Poon, with Pavel Afonine leading the research. AQuaRef uses machine learning (ML) tools developed at Carnegie Mellon integrated with the Phenix software to compute energy and forces for scientifically interesting proteins—making quantum-level refinement practical where it was previously impossible.

Of the 71 experiments that were tested in this study, AQuaRef produced higher quality structural information at a substantially lower computational cost while maintaining an equal or better fit to experimental data. In addition to the proof-of-concept results from this work, AQuaRef also correctly determined proton positions in DJ-1, a human protein linked to some forms of Parkinson’s Disease, the structure of which has been notoriously difficult to map. Now that the team has confirmed that quantum-level refinement of a 3D protein model structure is possible, they’re aiming to broaden the scope to include more diverse structures, such as those required for pharmaceutical drug design. And the potential impacts of this work reach far beyond human health, from better understanding the mechanisms of photosynthesis for enhanced crop productivity to mapping the proteins in plants as it relates to biofuel production.

“There is a near-infinite number of things that can benefit from a detailed understanding of these mechanisms and protein structure,” said Moriarty. “I’m excited to see how the paradigm shift that AQuaRef represents impacts the field of protein structure determination.”

This international team also included collaborators from the University of Wrocław, Poland, the University of Florida, and Pending.AI, Australia.

This work was funded by the National Institutes of Health as well as with support from the Phenix Industrial Consortium.

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Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

Newswise — As global demand for clothing continues to rise, the textile and apparel industry has become a significant contributor to climate change. In China, the world’s largest textile producer and exporter, rapid urbanization, income growth, and shifting consumption patterns have driven a surge in apparel demand. Traditional studies often focus on factory-level energy use, overlooking emissions embedded in supply chains, exports, and household consumption. This fragmented perspective limits the effectiveness of mitigation strategies. Moreover, fast fashion and short garment lifespans exacerbate resource use and waste. Based on these challenges, there is an urgent need to conduct in-depth research that captures the full carbon footprint of the textile industry and identifies scalable pathways for emission reduction.

Researchers from Nanjing University, in collaboration with international partners, reported (DOI: 10.1007/s11783-026-2109-9) on January 9, 2026, in Engineering Environment a comprehensive analysis of carbon emissions in China’s textile and apparel industry. Using national household consumption data and supply-chain input–output modeling, the team examined emission trends from 2000 to 2018 and projected future mitigation scenarios through 2035. Their study reveals how production, consumption, and exports jointly shape the sector’s carbon footprint and highlights practical strategies—particularly renewable energy and clothing recycling—to curb emissions while supporting sustainable industrial development.

The analysis shows that demand-side forces dominate carbon emissions in China’s textile industry. Household consumption and exports together account for roughly 85% of total emissions growth, far outweighing the contribution from direct energy use in factories. Urban households, in particular, generate more than four times the carbon emissions of rural households due to higher clothing consumption, underscoring the climate impact of lifestyle changes.

By constructing detailed carbon flow diagrams, the study identifies wet processing, electricity use, and long, fragmented supply chains as major emission hotspots. While electrification has reduced emissions from fossil fuels, carbon embodied in upstream sectors—such as chemicals, transportation, and logistics—continues to rise.

To explore mitigation pathways, the researchers modeled five future scenarios. Energy-saving technologies alone delivered limited reductions, while large-scale renewable energy adoption significantly lowered emissions by reducing carbon intensity across the entire supply chain. Clothing recycling emerged as another powerful lever, as extending garment lifespans directly reduces the need for new production. Most notably, a combined strategy integrating renewable energy and recycling could reduce total emissions by nearly 10% compared with a business-as-usual trajectory, effectively flattening long-term emission growth.

“This study shows that decarbonizing the textile industry is not just a technological challenge, but also a consumption challenge,” said the study’s corresponding author. “Focusing only on factories misses the bigger picture. Our results demonstrate that household demand, urban lifestyles, and export-oriented production play decisive roles in driving emissions. By aligning clean energy transitions with circular economy strategies—especially clothing recycling—we can achieve meaningful emission reductions without sacrificing economic vitality. These insights provide a scientific foundation for designing more effective and balanced climate policies.”

The findings have important implications for policymakers, industry leaders, and consumers. For governments, the study highlights the need to integrate demand-side measures—such as promoting clothing reuse and recycling—into climate strategies for the textile sector. For industry, it underscores the value of transitioning to renewable energy while redesigning supply chains to be shorter and more efficient. For consumers, the research quantifies how everyday clothing choices contribute to carbon emissions, reinforcing the climate benefits of longer garment lifespans. Together, these pathways suggest that a shift toward greener production and more responsible consumption can transform textiles from a climate liability into a key contributor to a low-carbon future.

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References

DOI

10.1007/s11783-026-2109-9

Original Source URL

https://doi.org/10.1007/s11783-026-2109-9

Funding information

The study was financially supported by the National Natural Science Foundation of China (Nos. 72304136, 72234003, and 72488101).

About Engineering Environment

Engineering Environment is the leading edge forum for peer-reviewed original submissions in English on all main branches of environmental disciplines. FESE welcomes original research papers, review articles, short communications, and views & comments. All the papers will be published within 6 months after they are submitted. The Editors-in-Chief are Academician Jiuhui Qu from Tsinghua University, and Prof. John C. Crittenden from Georgia Institute of Technology, USA. The journal has been indexed by almost all the authoritative databases such as SCI, EI, INSPEC, SCOPUS, CSCD, etc.

Newswise — The aviation industry accounts for a significant share of global carbon emissions. In response, the international community is expanding mandatory use of Sustainable Aviation Fuel (SAF), which is produced from organic waste or biomass and is expected to significantly reduce greenhouse gas emissions compared to conventional fossil-based jet fuel. However, high production costs remain a major challenge, leading some airlines in Europe and Japan to pass SAF-related costs on to consumers.

Against this backdrop, a research team led by Dr. Yun-Jo Lee at the Korea Research Institute of Chemical Technology (KRICT), in collaboration with EN2CORE Technology Co., Ltd., has successfully demonstrated an integrated process that converts landfill gas generated from organic waste—such as food waste—into aviation fuel.

Currently, the refining industry mainly produces SAF from used cooking oil. However, used cooking oil is limited in supply and is also used for other applications such as biodiesel, making it relatively expensive and difficult to secure in large quantities. In contrast, landfill gas generated from food waste and livestock manure is abundant and inexpensive. This study represents the first domestic demonstration of aviation fuel production using landfill gas as the primary feedstock.

Producing aviation fuel from landfill gas requires overcoming two major challenges: purifying the gas to obtain suitable intermediates and improving the efficiency of converting gaseous intermediates into liquid fuels. The research team addressed these challenges by developing an integrated process encompassing landfill gas pretreatment, syngas production, and catalytic conversion of syngas into liquid fuels.

EN2CORE Technology was responsible for the upstream processes. Landfill gas collected from waste disposal sites is desulfurized and treated using membrane-based separation to reduce excess carbon dioxide. The purified gas is then converted into synthesis gas—containing carbon monoxide and hydrogen—using a proprietary plasma reforming reactor, and subsequently supplied to KRICT.

KRICT applied the Fischer–Tropsch process to convert the gaseous syngas into liquid fuels. In this process, hydrogen and carbon react on a catalyst surface to form hydrocarbon chains. Hydrocarbons of appropriate chain length become liquid fuels, while longer chains form solid byproducts such as wax. By employing zeolite- and cobalt-based catalysts, KRICT significantly improved selectivity toward liquid fuels rather than solid byproducts.

A key innovation of this work is the application of a microchannel reactor. Excessive heat generation during aviation fuel synthesis can damage catalysts and reduce process stability. The microchannel reactor developed by the team features alternating layers of catalyst and coolant channels, enabling rapid heat removal and suppression of thermal runaway. Through integrated and modular design, the reactor volume was reduced by up to one-tenth compared to conventional systems. Production capacity can be expanded simply by adding modules.

For demonstration purposes, the team constructed an integrated pilot facility on a landfill site in Dalseong-gun, Daegu. The facility, approximately 100 square meters in size and comparable to a two-story detached house, successfully produced 100 kg of sustainable aviation fuel per day, achieving a liquid fuel selectivity exceeding 75 percent. The team is currently optimizing long-term operation conditions and further enhancing catalyst and reactor performance.

This achievement demonstrates the potential to convert everyday waste-derived gases from food waste and sewage sludge into high-value aviation fuel. Moreover, it shows that aviation fuel production—previously limited to large-scale centralized plants—can be realized at local landfills or small waste treatment facilities. The technology is therefore expected to contribute to the establishment of decentralized SAF production systems and strengthen the competitiveness of Korea’s SAF industry.

The research team noted that the work is significant in securing an integrated process technology that converts organic waste into high-value fuels. KRICT President Young-Kuk Lee stated that the technology has strong potential to become a representative solution capable of achieving both carbon neutrality and a circular economy.

The development of two catalysts enabling selective production of liquid fuels was published as an inside cover article in ACS Catalysis (November 2025) and in Fuel (January 2026).

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KRICT is a non-profit research institute funded by the Korean government. Since its foundation in 1976, KRICT has played a leading role in advancing national chemical technologies in the fields of chemistry, material science, environmental science, and chemical engineering. Now, KRICT is moving forward to become a globally leading research institute tackling the most challenging issues in the field of Chemistry and Engineering and will continue to fulfill its role in developing chemical technologies that benefit the entire world and contribute to maintaining a healthy planet. More detailed information on KRICT can be found at https://www.krict.re.kr/eng/

This research was supported by “Development of integrated demonstration process for the production of bio naphtha/lubricant oil from organic waste-derived biogas” (Project No. RS-2022-NR068680) through the National Research Foundation (NRF) funded by the Ministry of Science and ICT (MSIT), Republic of Korea.

Newswise — Lithium-ion batteries serve as the core energy storage devices in various industries and everyday products, including smartphones, electric vehicles, and ESS (energy storage systems). However, conventional lithium-ion batteries use liquid electrolytes, posing a risk of fire or explosion when subjected to external impact or overheating. Recent electric vehicle fire incidents have heightened concerns about their safety. As an alternative to overcome these limitations, ‘all-solid-state batteries’-which use non-flammable solid materials as electrolytes-are gaining attention as next-generation battery technology.

However, amorphous solid electrolytes-the core material for all-solid-state batteries-have faced limitations in analyzing lithium-ion transport mechanisms due to the irregularity of their internal structure. Consequently, performance improvements have been achieved empirically by altering electrolyte composition or compression conditions, making it difficult to systematically explain the causes of performance differences.

A research team led by Dr. Byungju, Lee at the Computational Science Research Center of the Korea Institute of Science and Technology (KIST, President Sang-Rok Oh) has identified key factors governing lithium ion movement in amorphous solid electrolytes through AI-based atomic simulations. The team analyzed lithium-ion movement by distinguishing it into ‘ease of movement between sites’ and ‘connectivity of movement paths’. They confirmed that overall performance is more significantly influenced by the difficulty of ions moving from one site to the next than by path connectivity.

In fact, while ion conductivity performance varied by up to fivefold depending on lithium ion mobility, the effect of pathway connectivity was limited to approximately a twofold difference. This provides a quantitative basis for interpreting performance variations that were previously difficult to explain due to the amorphous structure. Furthermore, the research team identified specific structural conditions that enhance lithium ion mobility. The higher the proportion of structures where four sulfur atoms surrounded a lithium ion, the faster the ion migration became. Optimal performance was achieved when the size of the internal void space fell within an appropriate range. Notably, excessively large voids actually hindered ion migration and degraded performance. This finding overturns the conventional wisdom that ‘lower density leads to higher conductivity’.

The results of this study can be directly applied to the design and manufacturing process of solid electrolytes for all-solid-state batteries. Simply controlling the internal structure by adjusting the electrolyte composition ratio or compression/molding conditions can improve ionic conductivity performance without requiring additional material changes, making it highly applicable in industrial settings. Furthermore, the analytical method proposed in this study can be extended to the development of various solid electrolyte materials. By pre-selecting high-performance candidate materials, it can dramatically enhance performance prediction and accelerate material development speed. This is expected to advance the commercialization of all-solid-state batteries in fields where safety and energy density are critical, such as electric vehicles and energy storage devices.

Dr. Byungju, Lee of KIST stated, “This research is significant in that it clearly identifies the key factors determining the performance of amorphous solid electrolytes.” He added, “As it presents design criteria enabling systematic improvement of material performance, we expect it to contribute to accelerating the commercialization of all-solid-state batteries.”

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KIST was established in 1966 as the first government-funded research institute in Korea. KIST now strives to solve national and social challenges and secure growth engines through leading and innovative research. For more information, please visit KIST’s website at https://kist.re.kr//eng/index.do

This research was conducted as part of KIST’s major projects and the Materials Global Young Connect Project (RS-2024-00407995), supported by the Ministry of Science and ICT (Minister Bae Kyung-hoon). The research findings were published in the latest issue of the international journal Advanced Energy Materials (IF 26.0, JCR field 2.5%).

Newswise — RICHLAND, Wash.—In a historic event decades in the making, the Hanford Site recently began immobilizing low-activity, radioactive waste by converting it into glass: a process known as vitrification. The event marked the successful start-up of Hanford’s Waste Treatment and Immobilization Plant, or “Vit Plant,” which will render millions of gallons of waste—generated by plutonium production during the Manhattan Project and Cold War—into glass for safe storage for thousands of years. The milestone also represents nearly 60 years of scientific contributions made by scientists and engineers at the Department of Energy’s Pacific Northwest National Laboratory.

“PNNL is proud to have played a pivotal role in advancing modern vitrification technology,” said Deb Gracio, PNNL director. “This milestone underscores the importance of innovation, collaboration, and scientific excellence in solving some of the world’s most pressing problems. It wouldn’t have been possible without a strong partnership among PNNL, DOE’s Hanford Field Office, Bechtel National Inc., the Office of Environmental Management, Hanford Tank Waste Operations & Closure, and of course our local community and stakeholders.”

Persistent and intense efforts by PNNL researchers—chemical engineers, computational scientists, materials scientists and chemists, among others—have advanced the science of vitrification since the 1960s, making this pursuit of materials science a defining element of PNNL’s history and impact. Not only have their innovations and collaborations with staff at the Vit Plant led to this historic achievement—their work has also informed vitrification operations around the world.

Birthplace of the melter

In the 1960s, researchers at PNNL engineered a technology that even today is among the most widely used tools for nuclear waste vitrification: the liquid-fed ceramic melter, which can be found amid vitrification operations on nearly every continent. Inside a melter, where temperatures can reach 2,100°F, low-activity waste is immobilized after being mixed with glass-forming chemicals—using formulas determined by a PNNL algorithm—then fed on top of a pool of molten glass. After the mixture is efficiently converted into glass, it is poured into containers and cooled to yield solid glass with radionuclides “locked” into the atomic structure of the glass. Simple at its core, carrying this process out in the real world can be anything but.

Each of the Hanford Site’s 177 one-million-gallon-capacity tanks contained a chemically unique and nonuniform waste. The composition of these wastes dictates both the behavior of the waste and which glass-forming chemicals are needed to make an acceptable glass. The “right” glass must not only incorporate and immobilize as much waste as possible—it also needs to be durable and avoid pitfalls like being difficult to transport through the plant, producing gas products in quantities that are challenging to treat or damaging to the plant’s infrastructure. Historically, designing a glass that strikes a balance among these goals meant spending a great deal of time fine-tuning the recipes.

For years, this process was carried out in a methodical, back-and-forth approach between glass design and performance testing. Scientists would consider the composition of a target waste, design a type of glass for the task, test its properties and adjust its composition until successful. In most facilities, this process can take months or even years.

“For the Vit Plant here in the Tri-Cities to operate successfully, we had to make it so that process happened on the order of minutes,” said John Vienna, PNNL materials scientist and lab fellow.

The challenge of vitrifying Hanford Site waste is made profoundly more challenging by the waste’s chemical complexity, according to Vienna, who has led a wide variety of research efforts in waste management, including the design of glasses used at the Hanford Site today. The Hanford Site’s waste is not only the most complex waste in the world but also the largest quantity ever to be targeted for vitrification.

From conventional to computational

Vienna, alongside his fellow scientists and colleagues from the Waste Treatment and Immobilization Plant with support from DOE glass scientist Albert Kruger and the Hanford Field Office, helped to solve the timeline challenge by innovating an entirely new approach to glass design. Instead of relying on the conventional approach carried out in a laboratory, they created a computational approach that utilizes modeling. Computer models are trained on hundreds of historical testing results and then prompted to make predictions by taking in the chemical makeup of waste to generate corresponding “recipes” that yield processable, economic and incredibly long-lasting glass.

Incorporating a partially computational approach has saved many years of effort and many millions of dollars for vitrification operations like those underway at DOE’s Savannah River Site in South Carolina. In the desert of southeastern Washington state, pretreated waste arrives at the beginning of the vitrification process in roughly 9,000-gallon batches. The waste is analyzed, and that information is fed into an algorithm that generates the corresponding glass design.

By comparison, a similar traditional approach was used at New York’s West Valley Demonstration Project site in the late 1990s, where glass design took roughly a decade. At the Hanford Site, this process now takes less than 120 minutes, and PNNL’s glass algorithm app is getting faster with each update.

Many current and former staff at PNNL have contributed to the design of the melters and other key equipment at the Vit Plant. The submerged bed scrubber, the air displacement slurry pump and melter technologies were all initiated and developed at PNNL. Will Eaton, a melter specialist, led portions of the Vit Plant melter designs and continues to lead research to improve melter materials and optimize melter processing. These innovations, along with PNNL contributions to designs led by other Vit Plant partners, make it possible for each melter to produce up to 15 metric tons of glass per day when operating at full capacity.

“PNNL has been an integral part of the Hanford Waste Treatment and Immobilization Plant. They have assisted in solving technical challenges and developed the vitrification glass recipes that are currently being processed in the Low-Activity Waste Facility,” said Chris Musick, general manager of the Bechtel-led Waste Treatment Completion Company LLC. “We look forward to growing our partnership with PNNL in the future as we move forward with treating tank waste and completing the high-level waste scope.”

The next generation

Today, PNNL scientists continue to support Hanford’s Waste Treatment and Immobilization Plant by analyzing pretreated and vitrified waste, as well as providing fast answers during the facility’s start-up. Seeing the first vitrified waste marked an especially satisfying career moment, said materials scientist José Marcial.

“It’s extremely exciting,” said Marcial, whose scientific career began with a vitrification-focused internship at PNNL as a high school student while studying at Kiona-Benton City High School then Columbia Basin College. “This shows that this isn’t just an academic exercise. It’s all of our effort being put to real use to benefit the country and our community. It’s truly an amazing time to be a part of this work.”

Similarly, Vienna, a mentor to Marcial, is enjoying the chance to witness the culmination of scientific effort spanning dozens of careers and thousands of scientific manuscripts and reports. “We’ve got three generations of researchers that have dedicated their careers to Hanford tank waste,” said Vienna. “Since the 1960s, there has always been a vitrification presence here at PNNL.”

Though vitrification at Hanford has begun, the work is far from over. Marcial and others are now focused on continuing near- and long-term support for the Waste Treatment and Immobilization Plant by contributing to improvements in overall efficiency, fine-tuning the glass algorithm performance and being part of the team addressing any emerging operational challenges. Additional PNNL researchers are applying their expertise to the broader cleanup mission, including grout waste form development, tank waste treatment, tank waste solids, the high-level waste facility and environmental remediation of subsurface soil and groundwater. As they look toward the future, Marcial looks toward the next generation of scientists.

Newswise — The Hong Kong Institute for Advanced Study (HKIAS) hosted its Annual General Meeting (AGM) on October 15, 2025, gathering Senior Fellows from across the globe to mark the Institute’s 10^th anniversary and engage in discussions centered on strategic advancements in research and international collaboration. Under the leadership of Chairman Professor Serge Haroche, the meeting commenced with a heart-warming welcome to the new appointed HKIAS Senior Fellows: Professor Françoise Combes, Professor Étienne Ghys, Professor Dame Madeleine Atkins, Professor Alessio Figalli and Professor Sylvie Méléard. The Executive Director, Professor Shuk Han Cheng, presented a comprehensive review of the recent initiatives undertaken by City University of Hong Kong (CityUHK) and HKIAS, highlighting current news, activities, collaborative interactions with faculty members between CityUHK and the home institutions of our Senior Fellows and the significant achievements of Senior Fellows to underscore a decade of excellence.

As a key component of the HKIAS 10^th anniversary celebration activities, HKIAS organised a series of distinguished lectures and round table discussion. These activities, which showcased the cutting-edge research contributions of our Senior Fellows across multitude of disciplines, were supported partially by the Kwang Hua Educational Foundation. Their reception among students and faculty at CityUHK and various academic institutions across Hong Kong highlighted a profound interest and active engagement within the academic community. 

13 October: Professor Serge Haroche, an esteemed Nobel laureate in Physics, unveiled the intricacies of laser and quantum physics. On the same day, Professor Pierre-Louis Lions, the 1994 recipient of the Fields Medal, engaged the audience with a discourse on the intersection of mathematics and artificial intelligence (AI).

14 October: Professor George Fu Gao, a world-renowned virologist, delivered an insightful lecture on AI-empowered vaccine and antibody development. Additionally, Professor Mu-ming Poo, a distinguished figure in neuroscience and brain-inspired technology illuminated the audience on brain science and its implications for AI development.

15 October: Professor Dame Madeleine Atkins, President Emeritus of Lucy Cavendish College at the University of Cambridge, led a Round Table Discussion on Additional Models of Research Grant Funding, with Mr David Foster, Executive Director of the Croucher Foundation, as the online guest speaker.

Throughout the AGM week, interdisciplinary meetings and networking events were integral to fostering mentorship opportunities and collaboration among HKIAS Senior Fellows, CityU Faculty members, emerging researchers and students from various disciplines.

These events reaffirmed HKIAS’s unwavering commitment to fostering global collaboration and scientific excellence over the past decade. As the Institute celebrated its 10^th anniversary, we look forward to organizing further initiatives that will enhance the international profile of the science and engineering community at CityUHK and explore new frontiers in research and collaboration.

For more details on the celebration events, please visit HKIAS past events.

Newswise — Ground-level ozone is a major air pollutant that threatens human health, ecosystems, and climate stability. Despite aggressive reductions in nitrogen oxides and primary volatile organic compounds, ozone levels continue to exceed air quality standards in many regions. This paradox reflects the complex and nonlinear nature of atmospheric photochemistry, where reactive radicals control ozone formation. Oxygenated volatile organic compounds (OVOCs) are key intermediates in this process, acting as both sources and sinks of radicals. However, most previous studies have measured only a small subset of OVOCs, leaving major uncertainties in radical budgets. Based on these challenges, there is a critical need to systematically investigate how a broader spectrum of OVOCs drives radical cycling and ozone formation.

In a study published (DOI: 10.1016/j.ese.2026.100659) in January 2026 in Environmental Science and Ecotechnology, researchers from the Southern University of Science and Technology, The Hong Kong Polytechnic University, Hong Kong Baptist University, Beijing University of Chemical Technology, and the University of Helsinki investigated how oxygenated volatile organic compounds shape atmospheric chemistry in background air over southern China. Combining intensive field observations with photochemical box modeling, the team examined the role of OVOCs in radical cycling and ozone formation. Their results show that commonly used models relying on limited OVOC measurements substantially misrepresent radical budgets and ozone production under real atmospheric conditions.

The study combined high-resolution field measurements with a detailed photochemical box model to quantify the role of OVOCs in atmospheric radical chemistry. When models were constrained using only three commonly measured OVOCs, simulated hydroxyl radical levels were overestimated by up to 100 percent. By contrast, including measurements of 23 OVOCs brought simulations into close agreement with observations.

The analysis revealed that OVOC photolysis contributed approximately 49–61 percent of total radical production, making it the dominant radical source in background air. Surprisingly, several OVOCs present at relatively low concentrations accounted for a disproportionate share of radical generation. Errors in simulating these compounds caused cascading biases in radical budgets, altering ozone formation pathways.

The study further showed that traditional chemical mechanisms systematically overestimate some OVOCs while underestimating others, masking offsetting errors that appear acceptable when only limited measurements are used. These hidden inaccuracies significantly affect predictions of ozone production rates and sensitivity regimes. Overall, the findings demonstrate that a narrow observational focus can lead to misleading conclusions about the drivers of ozone pollution.

“This work shows that what we don’t measure can matter more than what we do,” said one of the study’s senior authors. “OVOCs have often been treated as secondary products, but our results demonstrate that they are central to controlling radical chemistry and ozone formation. Without comprehensive OVOC observations, models may appear accurate while fundamentally misrepresenting atmospheric processes. Expanding OVOC measurements is therefore essential for designing effective air quality management strategies in regions struggling with persistent ozone pollution.”

These findings have important implications for air pollution control and atmospheric modeling worldwide. Strategies focused solely on reducing traditional ozone precursors may fail if OVOC-driven radical chemistry is ignored. Incorporating comprehensive OVOC measurements can improve model accuracy, guide emission control priorities, and help policymakers identify more effective mitigation pathways. The study also highlights the need to update chemical mechanisms and expand monitoring networks to include reactive OVOC intermediates. Ultimately, recognizing the hidden role of OVOCs may be key to resolving the long-standing challenge of persistent surface ozone pollution in both developing and industrialized regions.

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References

DOI

10.1016/j.ese.2026.100659

Original Source URL

https://doi.org/10.1016/j.ese.2026.100659

Funding information

This research was funded by the Hong Kong Research Grants Council via Theme-Based Research Scheme (T24-504/17-N) and General Research Fund (HKBU 15219621), the National Natural Science Foundation of China (42325504), the National Key Research and Development Program of China (2023YFC3706205), and the Shenzhen Science and Technology Program (JCYJ20220818100611024).

About Environmental Science and Ecotechnology

Environmental Science and Ecotechnology (ISSN 2666-4984) is an international, peer-reviewed, and open-access journal published by Elsevier. The journal publishes significant views and research across the full spectrum of ecology and environmental sciences, such as climate change, sustainability, biodiversity conservation, environment & health, green catalysis/processing for pollution control, and AI-driven environmental engineering. The latest impact factor of ESE is 14.3, according to the Journal Citation Reports^TM 2024.

Newswise — Georgia Institute of Technology has named Michael “Mike” Gazarik as the new director of the Georgia Tech Research Institute (GTRI) and a Georgia Tech senior vice president, effective February 16. 

A nationally respected aerospace and research leader, Gazarik has led large, complex research organizations across government, industry, and academia, shaping strategy, driving growth, and building institutions that deliver mission-critical innovation. With more than three decades of experience, his career reflects a deep ability to align technology with national priorities and guide organizations through periods of change and opportunity. 

A Georgia Tech alumnus, Gazarik currently serves as faculty director of the Engineering Management Program at the University of Colorado Boulder and as a part‑time staff member at the Johns Hopkins Applied Physics Laboratory. He previously held senior leadership roles at NASA, including director of engineering at NASA Langley Research Center and inaugural associate administrator for the Space Technology Mission Directorate (STMD). In industry, he spent eight years as vice president of engineering at Ball Aerospace, leading its strategic growth from an elite science contractor into a strategic national security asset that doubled in size.

“Mike Gazarik brings a rare combination of technical depth, executive leadership, and deep government experience,” said Tim Lieuwen, Georgia Tech’s executive vice president for Research. “He knows large research enterprises operate within the realities of policy and budget and has a proven ability to align technology with mission priorities while earning trust across stakeholders. We are excited to welcome Mike back to Georgia Tech to lead GTRI at a pivotal moment for research and innovation.”

GTRI employs more than 3,000 employees, conducting nearly $1 billion in annual research in areas such as autonomous systems, cybersecurity, electromagnetics, electronic warfare, modeling and simulation, sensors, systems engineering, and threat systems. GTRI’s renowned researchers combine science, engineering, economics, and policy to address challenges facing national security, industry, and society.

For nearly a century, GTRI has partnered with government and industry to deliver solutions to the most mission-critical challenges facing our nation,” said Georgia Tech President Ángel Cabrera. “We are proud to welcome Mike Gazarik to lead a crown jewel of our research enterprise and a crucial component of our nation’s science and technology fabric. His experience and leadership will strengthen GTRI’s ability to deliver on its mission and help make our nation safer, healthier, and more competitive.”

Gazarik is widely recognized for leading complex research enterprises with a focus on stability, strategic alignment, and mission impact. At NASA, he helped shape the agency’s science and technology enterprise during periods of fiscal constraint and technical risk, maintaining balance across broad mission areas and forming STMD to consolidate technology development. At Ball Aerospace, he guided significant growth and aligned strategy with evolving national security and civil space needs. His academic work has focused on preparing engineering leaders for mission-driven organizations — experience that aligns closely with GTRI’s role as a trusted partner to government and industry.

He earned a B.S. in electrical engineering from the University of Pittsburgh and an M.S. and Ph.D. in electrical engineering from Georgia Tech. Gazarik is a fellow of the American Institute of Aeronautics and Astronautics (AIAA), a former chair of AIAA’s Corporate Strategic Committee, and was elected to the AIAA Board of Trustees in 2025. His honors include NASA’s Outstanding Leadership Medal, the Silver Snoopy Award, the 2023 AIAA Rocky Mountain Section Educator of the Year, and recognition as Engineering Manager of the Year by the American Society of Engineering Management.

“GTRI has a remarkable legacy of delivering solutions that matter for the nation,” said Gazarik. “I’m honored to return to Georgia Tech and lead an organization that combines deep technical expertise with a mission-driven culture. My focus will be on listening, building on GTRI’s strengths, and ensuring we continue to advance research that makes a real difference for our partners and society.”

As director, Gazarik will lead GTRI’s multidisciplinary research enterprise, advancing its mission to deliver high‑impact science and technology solutions in support of national security, space systems, and critical societal needs.