Register – Page 98 – Chemistry and Physics

October 22, 2022October 23, 2022

Material called a mechanical neural network can learn and change its physical properties

A new type of material can learn and improve its ability to deal with unexpected forces thanks to a unique lattice structure with connections of variable stiffness, as described in a new paper by my colleagues and me.

The new material is a type of architected material, which gets its properties mainly from the geometry and specific traits of its design rather than what it is made out of. Take hook-and-loop fabric closures like Velcro, for example. It doesn’t matter whether it is made from cotton, plastic or any other substance. As long as one side is a fabric with stiff hooks and the other side has fluffy loops, the material will have the sticky properties of Velcro.

My colleagues and I based our new material’s architecture on that of an artificial neural network—layers of interconnected nodes that can learn to do tasks by changing how much importance, or weight, they place on each connection. We hypothesized that a mechanical lattice with physical nodes could be trained to take on certain mechanical properties by adjusting each connection’s rigidity.

To find out if a mechanical lattice would be able to adopt and maintain new properties—like taking on a new shape or changing directional strength—we started off by building a computer model. We then selected a desired shape for the material as well as input forces and had a computer algorithm tune the tensions of the connections so that the input forces would produce the desired shape. We did this training on 200 different lattice structures and found that a triangular lattice was best at achieving all of the shapes we tested.

Once the many connections are tuned to achieve a set of tasks, the material will continue to react in the desired way. The training is—in a sense—remembered in the structure of the material itself.

We then built a physical prototype lattice with adjustable electromechanical springs arranged in a triangular lattice. The prototype is made of 6-inch connections and is about 2 feet long by 1½ feet wide. And it worked. When the lattice and algorithm worked together, the material was able to learn and change shape in particular ways when subjected to different forces. We call this new material a mechanical neural network.

Besides some living tissues, very few materials can learn to be better at dealing with unanticipated loads. Imagine a plane wing that suddenly catches a gust of wind and is forced in an unanticipated direction. The wing can’t change its design to be stronger in that direction.

The prototype lattice material we designed can adapt to changing or unknown conditions. In a wing, for example, these changes could be the accumulation of internal damage, changes in how the wing is attached to a craft or fluctuating external loads. Every time a wing made out of a mechanical neural network experienced one of these scenarios, it could strengthen and soften its connections to maintain desired attributes like directional strength. Over time, through successive adjustments made by the algorithm, the wing adopts and maintains new properties, adding each behavior to the rest as a sort of muscle memory.

This type of material could have far reaching applications for the longevity and efficiency of built structures. Not only could a wing made of a mechanical neural network material be stronger, it could also be trained to morph into shapes that maximize fuel efficiency in response to changing conditions around it.

So far, our team has worked only with 2D lattices. But using computer modeling, we predict that 3D lattices would have a much larger capacity for learning and adaptation. This increase is due to the fact that a 3D structure could have tens of times more connections, or springs, that don’t intersect with one another. However, the mechanisms we used in our first model are far too complex to support in a large 3D structure.

The material my colleagues and I created is a proof of concept and shows the potential of mechanical neural networks. But to bring this idea into the real world will require figuring out how to make the individual pieces smaller and with precise properties of flex and tension.

We hope new research in the manufacturing of materials at the micron scale, as well as work on new materials with adjustable stiffness, will lead to advances that make powerful smart mechanical neural networks with micron-scale elements and dense 3D connections a ubiquitous reality in the near future.

October 22, 2022October 23, 2022

Navigating when GPS goes dark

Words like “tough” or “rugged” are rarely associated with a quantum inertial sensor. The remarkable scientific instrument can measure motion a thousand times more accurately than the devices that help navigate today’s missiles, aircraft and drones. But its delicate, table-sized array of components that includes a complex laser and vacuum system has largely kept the technology grounded and confined to the controlled settings of a lab.

Jongmin Lee wants to change that.

The atomic physicist is part of a team at Sandia that envisions quantum inertial sensors as revolutionary, onboard navigational aids. If the team can reengineer the sensor into a compact, rugged device, the technology could safely guide vehicles where GPS signals are jammed or lost.

In a major milestone toward realizing their vision, the team has successfully built a cold-atom interferometer, a core component of quantum sensors, designed to be much smaller and tougher than typical lab setups. The team describes their prototype in the academic journal Nature Communications, showing how to integrate several normally separated components into a single monolithic structure. In doing so, they reduced the key components of a system that existed on a large optical table down to a sturdy package roughly the size of a shoebox.

“Very high sensitivity has been demonstrated in the lab, but the practical matters are, for real-world application, that people need to shrink down the size, weight and power, and then overcome various issues in a dynamic environment,” Jongmin said.

The paper also describes a roadmap for further miniaturizing the system using technologies under development.

The prototype, funded by Sandia’s Laboratory Directed Research and Development program, demonstrates significant strides toward moving advanced navigation tech out of the lab and into vehicles on the ground, underground, in the air and even in space.

Ultrasensitive measurements drive navigational power

As a jet does a barrel roll through the sky, current onboard navigation tech can measure the aircraft’s tilts and turns and accelerations to calculate its position without GPS, for a time. Small measurement errors gradually push a vehicle off course unless it periodically syncs with the satellites, Jongmin said.

Quantum sensing would operate in the same way, but the much better accuracy would mean onboard navigation wouldn’t need to cross-check its calculations as often, reducing reliance on satellite systems.

Roger Ding, a postdoctoral researcher who worked on the project, said, “In principle, there are no manufacturing variations and calibrations,” compared to conventional sensors that can change over time and need to be recalibrated.

Aaron Ison, the lead engineer on the project, said to prepare the atom interferometer for a dynamic environment, he and his team used materials proven in extreme environments. Additionally, parts that are normally separate and freestanding were integrated together and fixed in place or were built with manual lockout mechanisms.

“A monolithic structure having as few bolted interfaces as possible was key to creating a more rugged atom interferometer structure,” Aaron said.

Furthermore, the team used industry-standard calculations called finite element analysis to predict that any deformation of the system in conventional environments would fall within required allowances. Sandia has not conducted mechanical stress tests or field tests on the new design, so further research is needed to measure the device’s strength.

“The overall small, compact design naturally leads towards a stiffer more robust structure,” Aaron said.

Photonics light the way to a more miniaturized system

Most modern atom interferometry experiments use a system of lasers mounted to a large optical table for stability reasons, Roger said. Sandia’s device is comparatively compact, but the team has already come up with further design improvements to make the quantum sensors much smaller using integrated photonic technologies.

“There are tens to hundreds of elements that can be placed on a chip smaller than a penny,” said Peter Schwindt, the principal investigator on the project and an expert in quantum sensing.

Photonic devices, such as a laser or optical fiber, use light to perform useful work and integrated devices include many different elements. Photonics are used widely in telecommunications, and ongoing research is making them smaller and more versatile.

With further improvements, Peter thinks the space an interferometer needs could be as little as a few liters. His dream is to make one the size of a soda can.

In their paper, the Sandia team outlines a future design in which most of their laser setup is replaced by a single photonic integrated circuit, about eight millimeters on each side. Integrating the optical components into a circuit would not only make an atom interferometer smaller, it would also make it more rugged by fixing the components in place.

While the team can’t do this yet, many of the photonic technologies they need are currently in development at Sandia.

“This is a viable path to highly miniaturized systems,” Roger said.

Meanwhile, Jongmin said integrated photonic circuits would likely lower costs and improve scalability for future manufacturing.

“Sandia has shown an ambitious vision for the future of quantum sensing in navigation,” Jongmin said.

October 21, 2022October 21, 2022

Mechanism of ketene transformation to gasoline catalyzed by H-SAPO-11

A joint research team led by Prof. Pan Xiulian, Prof. Bao Xinhe and Prof. Hou Guangjin from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences (CAS) revealed the reaction mechanism of ketene transformation to gasoline on the zeotype H-SAPO-11.

The study was published in Journal of the American Chemical Society on Oct. 3.

In 2016, the team proposed a new catalyst concept based on metal oxide-zeolite bifunctional catalysts and ketene intermediate was detected by highly sensitive synchrotron-based vacuum ultraviolet photoionization mass spectrometry during syngas conversion.

Further studies demonstrated that ketene can be converted to mixed light olefins over molecular zeotype SAPO-34 and transformed to ethene over the eight-membered ring side pocket acid sites of mordenite. Although ketene has also been identified as an important intermediate in other zeolite-catalyzed C1 chemistry, its transformation mechanism is not well understood.

In this study, the researchers studied ketene conversion over H-SAPO-11 employing kinetic analyses, in situ infrared spectroscopy, and solid-state nuclear magnetic resonance spectroscopy.

They found that ketene transformed to butene on the acid sites via either acetyl species following an acetic acid ketonization pathway or acetoacetyl species with keto-enol tautomerism following an acetoacetic acid decarboxylation pathway in the presence of water.

“Our study revealed experimentally for the first time on the reaction network of catalytic ketene conversion over zeotypes and may benefit the further understanding of C1 chemistry,” said Prof. Pan.

October 21, 2022October 21, 2022

Exploring the hidden charm of quark-gluon plasma

ALICE explores hidden charm of quark-gluon plasma — Illustration of the effect of quark–gluon plasma on the formation of charmonia in lead-nuclei collisions. When the plasma temperature increases, the more weakly bound ψ(2S) state is more likely to be “screened”, and thus not form, due to the larger number of quarks and gluons in the plasma (the colored circles). The increase in the number of charm quarks and antiquarks (c and c̄) can lead to the formation of additional charmonia by quark recombination. Credit: ALICE collaboration

Quark–gluon plasma is an extremely hot and dense state of matter in which the elementary constituents—quarks and gluons—are not confined inside composite particles called hadrons, as they are in the protons and neutrons that make up the nuclei of atoms. Thought to have existed in the early universe, this special phase of matter can be recreated at the Large Hadron Collider (LHC) in collisions between lead nuclei.

A new analysis from the international ALICE collaboration at the LHC investigates how different bound states of a charm quark and its antimatter counterpart, also produced in these collisions, are affected by quark–gluon plasma. The results open new avenues for studying the strong interaction—one of the four fundamental forces of nature—in the extreme temperature and density conditions of quark–gluon plasma.

Bound states of a charm quark and a charm antiquark, known as charmonia or hidden-charm particles, are held together by the strong interaction and are excellent probes of quark–gluon plasma. In the plasma, their production is suppressed due to “screening” by the large number of quarks and gluons present in this form of matter.

The screening, and thus the suppression, increases with the temperature of the plasma and is expected to affect different charmonia to varying degrees. For example, the production of the ψ(2S) state, which is ten times more weakly bound and 20% more massive than the J/ψ state, is expected to be more suppressed than that of the J/ψ state.

This hierarchical suppression is not the only fate of charmonia in quark–gluon plasma. The large number of charm quarks and antiquarks in the plasma—up to about a hundred in head-on collisions—also gives rise to a mechanism, called recombination, that forms new charmonia and counters the suppression to a certain extent.

This process is expected to depend on the type and momentum of the charmonia, with the more weakly bound charmonia possibly being produced through recombination later in the evolution of the plasma, and charmonia with the lowest (transverse) momentum having the highest recombination rate.

Exploring the hidden charm of quark-gluon plasma — A lead–lead collision event recorded by ALICE in 2015. Credit: ALICE collaboration

Previous studies, which used data from CERN’s Super Proton Synchrotron and subsequently from the LHC, have shown that the production of the ψ(2S) state is indeed more suppressed than that of the J/ψ. ALICE has also previously provided evidence of the recombination mechanism in J/ψ production. But, until now, no studies of ψ(2S) production at low particle momentum had been precise enough to provide conclusive results in this momentum regime, preventing a complete picture of ψ(2S) production from being obtained.

The ALICE collaboration has now reported the first measurements of ψ(2S) production down to zero transverse momentum, based on lead–lead collision data from the LHC collected in 2015 and 2018.

The measurements show that, regardless of particle momentum, the ψ(2S) state is suppressed about two times more than the J/ψ. This is the first time that a clear hierarchy in suppression has been observed for the total production of charmonia at the LHC. A similar observation was previously reported by the LHC collaborations for bound states of a bottom quark and its antiquark.

When further studied as a function of particle momentum, the ψ(2S) suppression is seen to be reduced towards lower momentum. This feature, which was previously observed by ALICE for the J/ψ state, is a signature of the recombination process.

Future higher-precision studies of these and other charmonia using data from LHC Run 3, which started in July, may lead to a definitive understanding of the modification of hidden-charm particles and, as a result, of the strong interaction that holds them together, in the extreme environment of quark–gluon plasma.

October 20, 2022October 21, 2022

Tapping hidden visual information: An all-in-one detector for thousands of colors

rainbows — Credit: Pixabay/CC0 Public Domain

Spectrometers are widely used throughout industry and research to detect and analyze light. Spectrometers measure the spectrum of light—its strength at different wavelengths, like the colors in a rainbow—and are an essential tool for identifying and analyzing specimens and materials. Integrated on-chip spectrometers would be of great benefit to a variety of technologies, including quality inspection platforms, security sensors, biomedical analyzers, health care systems, environmental monitoring tools, and space telescopes.

An international research team led by researchers at Aalto University has developed high-sensitivity spectrometers with high wavelength accuracy, high spectral resolution, and broad operation bandwidth, using only a single microchip-sized detector. The research behind this new ultra-miniaturized spectrometer was published today in the journal Science.

“Our single-detector spectrometer is an all-in-one device. We designed this optoelectronic-lab-on-a-chip with artificial intelligence replacing conventional hardware, such as optical and mechanical components. Therefore, our computational spectrometer does not require separate bulky components or array designs to disperse and filter light. It can achieve a high resolution comparable to benchtop systems but in a much smaller package,” says Postdoctoral Researcher Hoon Hahn Yoon.

“With our spectrometer, we can measure light intensity at each wavelength beyond the visible spectrum using a device at our fingertips. The device is entirely electrically controllable, so it has enormous potential for scalability and integration. Integrating it directly into portable devices such as smartphones and drones could advance our daily lives. Imagine that the next generation of our smartphone cameras could be fitted with hyperspectral cameras that outperform color cameras,” he adds.

Shrinking computational spectrometers is essential for their use in chips and implantable applications. Professor Zhipei Sun, the head of the research team, says, “Conventional spectrometers are bulky because they need optical and mechanical components, so their on-chip applications are limited. There is an emerging demand in this field to improve the performance and usability of spectrometers. From this point of view, miniaturized spectrometers are very important to offer high performance and new functions in all fields of science and industry.”

Professor Pertti Hakonen adds that “Finland and Aalto have invested in photonics research in recent years. For example, there has been great support from the Academy of Finland’s Center of Excellence on quantum technology, Flagship on Photonics Research and Innovation, InstituteQ, and the Otanano Infrastructure. Our new spectrometer is a clear demonstration of the success of these collaborative efforts. I believe that with further improvements in resolution and efficiency, these spectrometers could provide new tools for quantum information processing.”

October 20, 2022October 21, 2022

Developing stable water-splitting catalysts that don’t require expensive iridium

Synthesis and characterization of Ni-RuO². Credit: *Nature Materials* (2022). DOI: 10.1038/s41563-022-01380-5

Creating a hydrogen economy is no small task, but Rice University engineers have discovered a method that could make oxygen evolution catalysis in acids, one of the most challenging topics in water electrolysis for producing clean hydrogen fuels, more economical and practical.

The lab of chemical and biomolecular engineer Haotian Wang at Rice’s George R. Brown School of Engineering has replaced rare and expensive iridium with ruthenium, a far more abundant precious metal, as the positive-electrode catalyst in a reactor that splits water into hydrogen and oxygen.

The lab’s successful addition of nickel to ruthenium dioxide (RuO₂) resulted in a robust anode catalyst that produced hydrogen from water electrolysis for thousands of hours under ambient conditions.

“There’s huge industry interest in clean hydrogen,” Wang said. “It’s an important energy carrier and also important for chemical fabrication, but its current production contributes a significant portion of carbon emissions in the chemical manufacturing sector globally. We want to produce it in a more sustainable way, and water-splitting using clean electricity is widely recognized as the most promising option.”

Iridium costs roughly eight times more than ruthenium, he said, and it could account for 20% to 40% of the expense in commercial device manufacturing, especially in future large-scale deployments.

The process developed by Wang, Rice postdoctoral associate Zhen-Yu Wu and graduate student Feng-Yang Chen, and colleagues at the University of Pittsburgh and the University of Virginia is detailed in Nature Materials.

Water splitting involves the oxygen and hydrogen evolution reactions by which polarized catalysts rearrange water molecules to release oxygen and hydrogen. “Hydrogen is produced by the cathode, which is a negative electrode,” Wu said. “At the same time, it has to balance the charge by oxidizing water to generate oxygen on the anode side.”

Rice lab advances water-splitting catalystsEngineers develop stable devices that don’t require expensive iridium — A schematic shows the experimental water electrolyzer developed at Rice to use a nickel-doped ruthenium catalyst. Illustration by Zhen-Yu Wu

“The cathode is very stable and not a big problem, but the anode is more prone to corrosion when using an acidic electrolyte,” Chen said. “Commonly used transition metals like manganese, iron, nickel and cobalt get oxidized and dissolve into the electrolyte.

“That’s why the only practical material used in commercial proton exchange membrane water electrolyzers is iridium,” he said. “It’s stable for tens of thousands of hours, but it’s very expensive.”

Setting out to find a replacement, Wang’s lab settled on ruthenium dioxide for its known activity, doping it with nickel, one of several metals tried.

The researchers demonstrated that ultrasmall and highly crystalline RuO2 nanoparticles with nickel dopants, used at the anode, facilitated water-splitting for more than 1,000 hours at a current density of 200 milliamps per square centimeter with negligible degradation.

They tested their anodes against others of pure ruthenium dioxide that catalyzed water electrolysis for a few hundred hours before beginning to decay.

The lab is working to improve its ruthenium catalyst to slot into current industrial processes. “Now that we’ve reached this stability milestone, our challenge is to increase the current density by at least five to 10 times while still maintaining this kind of stability,” Wang said. “This is very challenging, but still possible.”

He sees the need as urgent. “The annual production of iridium won’t help us to produce the amount of hydrogen we need today,” Wang said. “Even using all the iridium globally produced will simply not generate the amount of hydrogen we will need if we want it to be produced via water electrolysis.

“That means we can’t fully rely on iridium,” he said. “We have to develop new catalysts to either reduce its use or eliminate it from the process entirely.”

October 19, 2022October 19, 2022

Exploring the decay processes of a quantum state weakly coupled to a finite-size reservoir

In quantum physics, Fermi’s golden rule, also known as the golden rule of time-dependent perturbation theory, is a formula that can be used to calculate the rate at which an initial quantum state transitions into a final state, which is composed of a continuum of states (a so-called “bath”). This valuable equation has been applied to numerous physics problems, particularly those for which it is important to consider how systems respond to imposed perturbations and settle into stationary states over time.

Fermi’s golden rule specifically applies to instances in which an initial quantum state is weakly coupled to a continuum of other final states, which overlap its energy. Researchers at the Centro Brasileiro de Pesquisas Físicas, Princeton University, and Universität zu Köln have recently set out to investigate what happens when a quantum state is instead coupled to a set of discrete final states with a nonzero mean level spacing, as observed in recent many-body physics studies.

“The decay of a quantum state into some continuum of final states (i.e., a ‘bath’) is commonly associated with incoherent decay processes, as described by Fermi’s golden rule,” Tobias Micklitz, one of the researchers who carried out the study, told Phys.org. “A standard example for this is an excited atom emitting a photon into an infinite vacuum. Current date experimentations, on the other hand, routinely realize composite systems involving quantum states coupled to effectively finite size reservoirs that are composed of discrete sets of final states, rather than a continuum.”

While several past studies have identified systems in which quantum states are coupled to finite size reservoirs, understanding the conditions under which this happens, allowing the finite size reservoirs to effectively act as “baths” is a challenging task. The key objective of the recent work by Micklitz and his colleagues was to better understand the process through which a quantum state decays when coupled to a finite size reservoir.

“Our starting point was to consider generic finite size reservoirs lacking any specific symmetries,” Micklitz explained. “Such systems usually show quantum chaotic behavior and can be modeled by random matrices for which powerful analytical tools are available.”

To carry out their analyses, Micklitz and his colleagues used a combination of effective matrix integral techniques, which are commonly used in studies applying random matrix theory, a theory that summarizes the different properties of matrices with entries drawn randomly from different probability distributions. To benchmark the results of their analyses, they then used exact diagonalization, a powerful numerical technique often used by physicists to study individual quantum many-body systems.

“Initially we hadn’t expected the decay into a finite size reservoir to be described by such a complex time-dependence,” Micklitz said. “We found that the probability to reside in the weakly coupled level shows a non-motonous time-dependence with initial decay, followed by a raise, before saturating to a constant value. The temporal profile follows (in a large regime of parameters) the ‘spectral form factor,’ a well-studied object in the quantum chaos community, which encodes information on energy level correlations in the reservoir. This makes much sense in retrospective.”

Now published in Physical Review Letters, the recent study by this team of researchers offers a fully analytic description of a crucial and fundamental physics problem. More specifically, it offers a connection between the problem of how a quantum state decays into a set of discrete final states to the statistics associated with energy levels and wave functions in chaotic quantum systems.

“We relate the temporal profile of the probability of residence to the spectral form factor, and the ratio of the probability’s minimum and saturation values to the statistics of reservoir-eigenfunctions,” Micklitz added. “Our work focuses on a fundamental but also rather elementary example of relaxation into a finite size reservoir. We are now trying to address more complex systems, such as ensembles of spins coupled to a quantum dot. Hopefully, progress can be made using similar methods as those employed in our recent paper.”

October 19, 2022October 19, 2022

Converting carbon dioxide to solid minerals underground for more stable storage

A new scientific review article in Nature Reviews Chemistry discusses how carbon dioxide (CO₂) converts from a gas to a solid in ultrathin films of water on underground rock surfaces. These solid minerals, known as carbonates, are both stable and common.

“As global temperatures increase, so does the urgency to find ways to store carbon,” said Pacific Northwest National Laboratory (PNNL) Lab Fellow and co-author Kevin Rosso. “By taking a critical look at our current understanding of carbon mineralization processes, we can find the essential-to-solve gaps for the next decade of work.”

Mineralization underground represents one way to keep CO₂ locked away, unable to escape back into the air. But researchers first need to know how it happens before they can predict and control carbonate formation in realistic systems.

“Mitigating human emissions requires fundamentally understanding how to store carbon,” said PNNL chemist Quin Miller, co-lead author of the scientific review featured on the journal cover. “There is a pressing need to integrate simulations, theory, and experiments to explore mineral carbonation problems.”

Below the ground and in the water

Instead of emitting CO₂ into the air, one option is to pump it into the ground. Putting CO₂ deep underground theoretically sequesters the carbon away. However, gas leaks remain a concern. But if that CO₂ gas can be pumped into rocks rich in metals like magnesium and iron, the CO₂ can be transformed into stable and common carbonate minerals. PNNL’s Basalt Pilot Project at Wallula is a field site dedicated to studying CO₂ storage in carbonates.

Although these subsurface environments are generally dominated by water, the conversion of gaseous carbon dioxide to solid carbonate can also occur when injected CO₂ displaces that water, creating extremely thin films of residual water in contact with rocks. But these highly confined systems behave differently than CO₂ in contact with a pool of water.

In thin films, the ratio of water and CO₂ controls the reaction. Small amounts of metal leach out from the rocks, reacting both in the film and on the rock surface. This leads to the creation of new carbonate materials.

Previous work led by Miller, summarized in the review, showed that magnesium behaves similarly to calcium in thin water films. The nature of the water film plays a central role in how the system reacts.

Understanding how and when these carbonates form requires a combination of laboratory experiments and theoretical modeling studies. Laboratory work allows researchers to tune the ratio of water to CO₂ and watch carbonates form in real time. Teams can see which specific chemicals are present at different points in time, providing essential information about reaction pathways.

However, laboratory-based work has its limits. Researchers cannot observe individual molecules or see how they interact. Chemistry models can fill in that gap by predicting how molecules move in exquisite detail, giving conceptual backbone to experiments. They also allow researchers to study mineralization in hard to experimentally access conditions.

“There are important synergies between models and laboratory or field studies,” said MJ Qomi, a professor at the University of California, Irvine and co-lead author of the article. “Experimental data grounds models in reality, while models provide a deeper level of insight into experiments.” Qomi has collaborated with the PNNL team for three years, and plans to study carbonate mineralization in adsorbed water films.

From fundamental science to solutions

The team outlined key questions that need answering to make this form of carbon storage practical. Researchers must develop knowledge of how minerals react under different conditions, particularly in conditions that mimic real storage sites, including in ultrathin water films. This should all be done through an integrated combination of modeling and laboratory experiments.

Mineralization has the potential to keep carbon safely stored underground. Knowing how CO₂ will react with different minerals can help make sure that what gets pumped underneath the surface stays there. The fundamental science insights from mineralization work can lead to practical CO₂ storage systems. The Basalt Pilot Project represents an important study site that bridges small-scale basic science and large-scale research applications.

“This work combines a focus on fundamental geochemical insights with a goal of solving crucial problems,” said Miller. “Without prioritizing decarbonization technologies, the world will continue warming to a degree humanity cannot afford.”

Miller, Rosso, and Todd Schaef were the PNNL authors of this study. This work was performed in collaboration with MJ Qomi and Siavash Zare of the University of California, Irvine as well as John Kaszuba of the University of Wyoming.

October 18, 2022October 18, 2022

Steel mill gases transformed into bioplastic

Plastic waste from food deliveries is rapidly polluting the environment. An alternative that has emerged is bioplastic, which is also called biodegradable plastic. Bioplastic that uses eco-friendly raw materials emits less pollutants during the production process and has natural decomposition properties. Recently, a Korea-Spain joint research team recreated bioplastic from waste byproducts from gas fermentation from steel mills.

Through joint research with Spain’s Center for Research in Agricultural Genomics (CRAG), a research team led by Professor Gyoo Yeol Jung, Ph.D. candidates Dae-yeol Ye and Jo Hyun Moon, and Dr. Myung Hyun Noh in the Department of Chemical Engineering at POSTECH has developed a technology to generate artificial enzymes from E. coli. The joint research then succeeded in mass-producing itaconic acid, a source material for bioplastic, from acetic acid in E. coli. This study is published in Nature Communications.

Itaconic acid produced by fungi with membrane-enclosed organelles is used as a raw material for various plastics, as well as cosmetics and antibacterial agents. Although its global market value is estimated high at around 130 billion KRW (USD$91 million) this year, its production and utilization have been limited due to the complex production process and high cost of production.

For this reason, studies are being actively conducted to produce itaconic acid with industrial microorganisms such as E. coli. Although E. coli can be produced using inexpensive raw materials and is easy to culture, additional raw materials or processes were required to produce itaconic acid since it lacks membrane-enclosed organelles.

Using biosynthesis, the joint research team developed an artificial enzyme to pave the way for E. coli to directly produce itaconic acid without membrane-enclosed organelles. The research results showed that the newly developed enzyme can be used in E. coli to produce itaconic acid. With this technology, it is now possible to build a microbial cell factory that can easily produce itaconic acid from cheap and various raw materials.

This research result is evaluated as a key original technology for producing itaconic acid from byproduct of gas fermentation products from steel mills, seaweed, as well as agricultural and fishery byproducts such as lignocellulosic biomass. By replacing the raw material from petrochemicals with biosynthesized itaconic acid, the new technology is anticipated to contribute to a carbon-neutral society and significantly expand the itaconic acid market.

October 18, 2022October 18, 2022

Exploring light-driven molecular swing

Calculated coherence and energy transfer ratios. Calculated vibrational molecular coherence in the symmetric stretching vibrational mode of the DMSO2 molecule in solution displayed in a frame rotating with the vibrational eigenfrequency. The calculations are done with a the compressed pulse using the RWA, b the compressed pulse without the RWA, c the chirped pulse using the RWA, and d the chirped pulse without the RWA. The red curves include relaxation; the blue curves do not include relaxation. Each bump of the cycloid in b corresponds to one half-cycle of the electric field, showing that energy transfer from the excitation field to the molecular system is completed after 3 to 4 field cycles in the case of the FCE. In d, the time points that are maxima of CET(t) caused by the symmetric stretching vibration are marked with black dots. e Re-emitted (orange) and maximum absorbed (green) fraction of the impinging pulse energy versus concentration. The results were obtained from the impulsive-regime model (see Supplementary Information) with the FCE and ab initio Lorentz parameters. The solid lines include direct interactions with the surrounding water and the screening effect of the polarizable continuum, the dashed lines only the latter, and the dotted lines neither. For small concentrations, the maximum absorbed energy scales linearly with concentration. In contrast, the coherent re-emission, containing the spectroscopic information, scales quadratically with concentration. Credit: Nature Communications (2022). DOI: 10.1038/s41467-022-33477-5

When light impinges on molecules, it is absorbed and re-emitted. Advances in ultrafast laser technology have steadily improved the level of detail in studies of such light-matter interactions.

FRS, a laser spectroscopy method in which the electric field of laser pulses repeating millions of times per second is recorded with time resolution after passing through the sample, now provides even deeper insights: Scientists led by Prof. Dr. Regina de Vivie-Riedle (LMU/Department of Chemistry) and PD Dr. Ioachim Pupeza (LMU/Department of Physics, MPQ) show for the first time in theory and experiment how molecules gradually absorb the energy of the ultrashort light pulse in each individual optical cycle, and then release it again over a longer period of time, thereby converting it into spectroscopically meaningful light.

The study elucidates the mechanisms that fundamentally determine this energy transfer. It also develops and verifies a detailed quantum chemical model that can be used in the future to quantitatively predict even the smallest deviations from linear behavior.

A child on a swing sets it in motion with tilting movements of the body, which must be synchronized with the swing movement. This gradually adds energy to the swing, so that the deflection of the swing increases over time. Something similar happens when the alternating electromagnetic field of a short laser pulse interacts with a molecule, only about 100 trillion times faster: When the alternating field is synchronized with the vibrations between the atoms of the molecule, these vibration modes absorb more and more energy from the light pulse, and the vibration amplitude increases.

When the exciting field oscillations are over, the molecule continues to vibrate for a while—just like a swing after the person stops the tilting movements. Like an antenna, the slightly electrically charged atoms in motion then radiate a light field. Here, the frequency of the light field oscillation is determined by properties of the molecule such as atomic masses and bond strengths, which allows for an identification of the molecule.

Researchers from the attoworld team at MPQ and LMU, in collaboration with LMU researchers from the Department of Chemistry (Division of Theoretical Femtochemistry), have now distinguished these two constituent parts of the light field—on the one hand, the exciting light pulses, and on the other, the decaying light field oscillations—using time-resolved spectroscopy. In doing so, they investigated the behavior of organic molecules dissolved in water.

“While established laser spectroscopy methods usually only measure the spectrum and thus do not allow any information about the temporal distribution of the energy, our method can precisely track how the molecule absorbs a little more energy with each subsequent oscillation of the light field,” says Ioachim Pupeza, head of the experiment.

That the measurement method allows this temporal distinction is best illustrated by the fact that the scientists repeated the experiment, changing the duration of the exciting pulse but without changing its spectrum. This makes a big difference for the dynamic energy transfer between light and the vibrating molecule: Depending on the temporal structure of the laser pulse, the molecule can then absorb and release energy several times during the excitation.

In order to understand exactly which contributions are decisive for the energy transfer, the researchers have developed a supercomputer-based quantum chemical model. This can explain the results of the measurements without the aid of measured values. “This allows us to artificially switch off individual effects such as the collisions of the vibrating molecules with their environment, or even the dielectric properties of the environment, and thus elucidate their influence on the energy transfer,” explains Martin Peschel, one of the first authors of the study.

In the end, the energy re-emitted during the decaying light field oscillations is decisive for how much information can be obtained from a spectroscopic measurement. The work thus makes a valuable contribution to better understanding the efficiency of optical spectroscopies, for example with regard to molecular compositions of fluids or gases, with the objective of improving it further and further.

The research is published in Nature Communications.