Solid oxide fuel cells convert chemical energy directly into electricity and can run on hydrogen, natural gas, or biogas, producing only water as the main product when hydrogen is the fuel. Despite these advantages, conventional devices face a persistent limitation: their electrolytes must be heated to very high temperatures to conduct oxide ions efficiently. Commercially available electrolytes such as yttria-stabilized zirconia, commonly known as YSZ, typically require operating temperatures of roughly 700 to 1,000 °C. At those temperatures, materials degrade faster, manufacturing becomes more expensive, and compatibility problems arise between the different components of the cell.

Lowering the operating temperature to between 200 and 500 °C has long been a goal of materials scientists, yet the search has been unexpectedly difficult. Electrolyte materials that simultaneously combine sufficient oxide-ion conductivity, chemical stability, and negligible chemical expansion are extremely rare in this window. The temperature range has become known as the Norby gap, and bridging it is considered an important challenge not only for solid oxide fuel cells but also for a wide variety of chemical and energy-conversion processes. The new oxybromide sits squarely inside this gap, which is precisely why the researchers consider it a breakthrough.

The path to the discovery began with an earlier compound. In previous work, the same team reported high oxide-ion conduction in a related Sillén oxychloride, Bi_1.9Te_0.1LaO_4.05Cl, but its conductivity fell short of the levels needed for the Norby gap. Building on that result, the researchers replaced the chloride ion with a larger and more polarizable bromide ion, synthesizing Bi_1.9Te_0.1LaO_4.05Br and systematically investigating its crystal structure and transport properties. The substitution proved decisive, unlocking conductivity far beyond that of the oxychloride precursor.

The performance figures are striking when compared with established electrolytes. YSZ and lanthanum strontium gallium magnesium oxide, known as LSGM, require temperatures of 644 °C and 534 °C respectively to reach the same 0.01 S cm⁻¹ bulk conductivity that the new oxybromide delivers at 233 °C. The material’s oxide-ion conductivity even exceeds the proton conductivity reported for several representative proton-conducting ceramics. Beyond raw conductivity, the compound exhibits high chemical stability across a range of atmospheres, including dry and wet oxidizing, reducing, and CO₂ environments at temperatures up to 300 °C, and it shows negligible chemical expansion, a property that matters greatly for the long-term mechanical integrity of fuel cell stacks.

Crystal structure analysis revealed a Sillén-type architecture in which highly conductive triple fluorite-like slabs are sandwiched between bromine layers. This layered arrangement creates a distinctive structural environment that supports fast oxide-ion transport, and the researchers regard the sandwich structure itself as a new material-design principle. By engineering similar slabs between different halide layers, other members of the family can potentially be tuned in the same way. Consistent with this idea, the team synthesized additional Sillén oxybromides and iodides that also demonstrated high electrical conductivity, suggesting the broader family offers a promising platform for fast oxide-ion conductors.

The most surprising result concerns the microscopic mechanism of ion movement. Bi_1.9Te_0.1LaO_4.05Br contains excess oxygen, reflected in its oxygen content of 4.05, and conventional wisdom holds that such excess-oxygen conductors should transport oxide ions predominantly through an interstitialcy diffusion mechanism, in which interstitial ions displace lattice ions along the conduction path. Instead, through a combination of diffraction studies, first-principles calculations, and ab initio molecular dynamics simulations, the team found that both oxygen vacancies and interstitial oxide ions coexist in the material, with vacancies at lattice oxygen sites and excess ions at interstitial sites, and that the transport proceeds by a vacancy-mediated mechanism. Oxide ions migrate from a lattice site to a neighboring vacant lattice site, moving through vacancies despite the presence of surplus oxygen atoms and interstitial ions.

This finding challenges the widely accepted picture of how oxide ions should behave in excess-oxygen materials. “Our findings demonstrate that strategically engineered oxygen vacancies enable ultrafast oxide-ion transport even in materials containing excess oxygen atoms,” Yashima said. “This overturns a widely accepted picture of how oxide ions should move in excess-oxygen materials and opens a new direction for designing fast oxide-ion conductors.” The result suggests that materials previously expected to rely on interstitialcy diffusion may instead be optimized by deliberately introducing and controlling vacancies, expanding the design space available to solid-state ionics researchers.

The research was a collaborative effort involving graduate students Yusuke Kanenori and Hidetoshi Udagawa along with Assistant Professors Kei Saito, Yuichi Sakuda, and Kotaro Fujii from Science Tokyo; Professor Tatsumi Ishihara and Dr. Maksymilian Kluczny from Kyushu University in Japan; Professor Stephen Skinner and Dr. Mudasir A. Yatoo from Imperial College London; and Professor Kazuhiro Mori from the High Energy Accelerator Research Organization (KEK) and J-PARC in Japan. The authors declare no competing interests, and the study was an experimental investigation combining synthesis, diffraction, computational modeling, and electrochemical characterization.

Important work remains before the material can reach practical devices. The researchers note that the total conductivity of the compound is currently lower than its bulk conductivity because of grain-boundary resistance, meaning that optimization of the microstructure, including grain growth and densification, will be essential for translating the exceptional bulk performance into real electrolyte performance. Nevertheless, the team believes the discovery could lay the foundation for a new research field it calls Oxide Ionics. “This discovery establishes a new foundation for designing novel oxide-ion conductors based on vacancy-mediated transport in materials with excess oxygen atoms,” Yashima said. “By sandwiching highly oxide-ion conductive triple fluorite-like slabs by Br layers, we may be able to develop a broader family of novel oxide-ion conductors for low-temperature SOFCs, solid oxide electrolysis cells, and other technologies.” If that vision is realized, fuel cells capable of efficient operation at a few hundred degrees Celsius could move significantly closer to commercial reality.

Subject of Research: Vacancy-mediated ultrafast oxide-ion conduction in excess-oxygen Sillén oxybromides for low-temperature solid oxide fuel cells

Article Title: Novel ultrafast solid oxide-ion conductors for low-temperature fuel cells

Article References: Novel ultrafast solid oxide-ion conductors for low-temperature fuel cells. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: oxide-ion conductors, Sillén oxyhalides, solid oxide fuel cells, Norby gap, bismuth oxybromide, oxygen vacancies, ionic conductivity, electrolytes, low-temperature fuel cells, crystal structure, ab initio molecular dynamics, chemical stability

The core insight of the paper is that knowledge gained from low-entropy systems, in which each crystal site is occupied by just one or two elements, can be transferred to high-entropy systems where the same sites host a blend of many elements. The team began by enumerating 1596 possible combinations of cesium-based chloride double perovskites, a lead-free family of semiconductors with the general formula Cs2BB’Cl6, where two different metal cations share the octahedral B-site of the crystal lattice. Rigorous stability screening narrowed this list to 275 viable semiconductors. From that curated set, the researchers extracted combinatorial rules and stability relationships, such as which pairings of cations are geometrically and thermodynamically compatible, and used them to define a rules-based element pool for constructing five-element B-site alloys.

On top of that constrained design space, the team layered an explainable machine-learning architecture that combines a Stacking ensemble with a Generalized Additive Model. Stacking blends the predictions of multiple base learners through a meta-model, capturing nonlinear interactions between elemental descriptors, while the additive component expresses the bandgap as a sum of smooth, interpretable functions of individual features. The result is a model that achieves a coefficient of determination, or R-squared, of 0.91 on its test set, meaning it accounts for roughly ninety-one percent of the variance in bandgap values across unseen compositions. Crucially, the additive framework does not behave like a black box: it yields closed-form formulas that quantitatively describe how each elemental property, most notably Pauling electronegativity, denoted by the Greek letter chi, shifts the energy gap between the material’s valence and conduction bands.

Bandgap is the single most important number in photovoltaics. It determines which slice of the solar spectrum a material can absorb, and the theoretical maximum efficiency of a single-junction solar cell peaks when the bandgap sits near 1.3 to 1.4 electron-volts. Most lead-free chloride double perovskites, however, have gaps far too wide to harvest sunlight efficiently, often exceeding two electron-volts. The new workflow revealed that by mixing five cations on the B-site, designers can either compress the gap dramatically or hold it steady, depending on how the electronegativities of the chosen elements are balanced. Because the descriptor-response functions are explicit, chemists can read off, in advance, roughly what bandgap a given five-element cocktail should produce, rather than synthesizing it and hoping for the best.

To confirm that the machine-learning predictions correspond to real physics, the authors turned to density-functional theory, the workhorse quantum-mechanical method of computational materials science. Two candidates emerged with strikingly different behaviors. The first, Cs2{ScNaInBGa}2Cl6, a compound whose B-site hosts scandium, sodium, indium, boron and gallium, showed bandgap compression from 2.96 down to 0.49 electron-volts, a reduction of nearly two and a half electron-volts that would allow the material to absorb light across almost the entire visible and near-infrared spectrum. The second, Cs2{BaZnCdSiGe}2Cl6, combining barium, zinc, cadmium, silicon and germanium, exhibited what the authors call compensatory alloying: its bandgap was retained almost perfectly, moving only from 1.56 to 1.57 electron-volts as the five elements’ opposing contributions canceled one another out. That 1.5-electron-volt regime is squarely within the sweet spot for high-efficiency single-junction photovoltaics.

Bandgap tuning alone is worthless if the resulting crystal falls apart, so the team subjected both candidates to a battery of stability tests. Tolerance-factor analysis, a geometric criterion relating the sizes of the ions to the stability of the perovskite framework, confirmed that both compositions fit the structural window in which the three-dimensional lattice can form. Calculated formation energies came out negative for both materials, indicating that they are thermodynamically favored to crystallize rather than decompose into competing phases. The researchers also evaluated the role of configurational entropy, the thermodynamic driver that stabilizes multielement alloys: the temperature-times-entropy term, T-delta-S, contributes a genuine stabilizing free-energy bonus that helps offset the strain of mixing five dissimilar cations on one lattice site.

The most demanding test was ab initio molecular dynamics, a simulation technique that tracks every atom in a crystal as it vibrates at finite temperature. The team ran 8-picosecond trajectories at 300 kelvin, roughly room temperature, for both candidate compositions. Throughout those simulations the perovskite frameworks remained intact, with no spontaneous bond breaking, cation migration or structural collapse. While 8 picoseconds is a fleeting instant compared with the years a solar panel must survive outdoors, such simulations are a standard first filter for weeding out compositions that would never survive synthesis, and both candidates passed cleanly.

What makes the O2O paradigm notable beyond its specific predictions is its philosophy. High-entropy materials research has exploded in recent years because mixing many elements confers remarkable robustness, tunability and, in some cases, entirely new functionalities, from entropy-stabilized oxides to high-entropy thermoelectrics. Yet the combinatorial explosion is brutal: with dozens of plausible cations and five slots to fill, the number of candidate compositions runs into the millions, far beyond what even the fastest high-throughput DFT pipelines can evaluate. By using interpretable rules harvested from the low-entropy regime as a prior, the new workflow effectively shrinks the search space before the expensive models ever run, a design pattern that echoes the way human chemists have always reasoned, but at machine scale and with quantified confidence.

The emphasis on explainability also matters for trust and reuse. Many state-of-the-art machine-learning models for materials, including graph neural networks, deliver impressive accuracy but offer little physical insight, making it hard for experimentalists to know when a prediction can be extrapolated safely. The Stacking-plus-GAM approach used here produces explicit descriptor-response curves, so the electronegativity dependence of the bandgap can be inspected, criticized and refined by any reader. The authors have made the entire pipeline reproducible, releasing source code, sample inputs and documentation through a public repository, which lowers the barrier for other groups to apply the same strategy to different perovskite chemistries, such as bromides, iodides or hybrid organic-inorganic frameworks.

Considerable work remains before any of these compositions light up a rooftop. The study’s candidates are prioritized hypotheses, not synthesized compounds, and the authors themselves frame the outcome as concrete composition rules, interpretable functions and a shortlist for further phase-stability assessment and experimental evaluation. Growing phase-pure five-element double perovskite crystals, verifying their gaps optically, and testing them in actual device architectures will take years. But the study offers a credible answer to one of the field’s most persistent questions: how to search an astronomically large compositional space without drowning in it. If the low-entropy-to-high-entropy knowledge transfer proves general, the approach could accelerate the discovery of lead-free, stable, spectrally matched absorbers, precisely the combination of properties that next-generation photovoltaics have been waiting for.

Subject of Research: Machine-learning-guided bandgap engineering of high-entropy lead-free chloride double perovskites for photovoltaics

Article Title: Intelligent bandgap engineering for high-efficiency perovskite photovoltaics: directing high-entropy optimization through low-entropy knowledge synergy

Article References: Hu, W., Jiang, J., Peng, L., Shi, T., Liu, X., & Lin, J. (2026). Intelligent bandgap engineering for high-efficiency perovskite photovoltaics: directing high-entropy optimization through low-entropy knowledge synergy. Journal of Materials Science. https://doi.org/10.1007/s10853-026-13827-0

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13827-0

Keywords: high-entropy perovskites, bandgap engineering, photovoltaics, machine learning, double perovskite, density functional theory, lead-free solar materials, explainable AI, configurational entropy, ab initio molecular dynamics, chloride perovskite, materials discovery

The centerpiece of the new analysis is a dehydrogenation mechanism that had never previously been identified for this material. Rather than breaking down completely into elemental potassium, nickel, and hydrogen, the simulation results reveal that K2NiH6 releases its hydrogen through a thermodynamically favorable partial decomposition reaction, producing two units of potassium hydride, metallic nickel, and two molecules of hydrogen gas. This distinction is far more than a chemical curiosity. By stopping short of the full decomposition pathway, the material energetically bypasses the difficult step of reducing potassium back to its elemental form, which would otherwise impose a severe thermodynamic penalty. The consequence is a hydrogen diffusion activation energy of just 0.609 electronvolts, a remarkably low barrier that translates directly into fast hydrogen release kinetics at temperatures close to room temperature.

Indeed, the calculated equilibrium desorption temperature for K2NiH6 comes out at 296.01 kelvin, or roughly 23 degrees Celsius, essentially ambient conditions. For a field in which many traditional metal hydrides demand heating to several hundred degrees Celsius before they will give up their stored hydrogen, this figure is remarkable. It means that a storage tank built around this material could, in principle, release hydrogen without any external heating apparatus, simplifying system design, reducing weight, and eliminating parasitic energy losses that currently erode the efficiency of hydrogen-powered vehicles. The researchers note that this near-ambient dehydrogenation capability is directly compatible with the practical operational targets set by the United States Department of Energy for onboard hydrogen storage in light-duty vehicles, a benchmark that has proven notoriously difficult for candidate materials to meet.

Capacity figures matter just as much as temperature, and here the study delivers a nuanced but encouraging assessment. At the level of the pure material, K2NiH6 offers a theoretical volumetric hydrogen capacity of 51.68 grams per liter and a gravimetric capacity of 2.82 weight percent. The volumetric number is particularly significant. Because hydrogen is the lightest element in the universe, packing enough of it into a tank of practical size is the central engineering problem of hydrogen mobility, and a material that stores hydrogen densely within its own crystal lattice provides a compact intrinsic baseline that compressed gas and even liquid hydrogen struggle to match at comparable pressures and temperatures. While the gravimetric capacity is modest by material standards, the authors emphasize that this value provides a robust volumetric margin for future system-level engineering, where tank architecture, heat management, and buffer materials can be optimized around the hydride’s intrinsic density advantage.

Perhaps the most unexpected finding of the study lies not in chemistry but in mechanics. Any solid-state hydrogen storage material must survive thousands of charging and discharging cycles, during which the absorption and release of hydrogen repeatedly swell and contract the crystal lattice. In brittle materials, these volumetric strains nucleate microcracks that progressively destroy the storage bed, degrading performance and eventually causing mechanical failure. The mechanical analysis performed by the Turkish team shows that K2NiH6 is exceptionally well suited to endure this abuse. The material exhibits a Pugh ratio of 1.78, a value well above the threshold that separates ductile from brittle behavior, indicating that it deforms plastically rather than fracturing under stress.

Even more remarkably, the calculations reveal that the hydride possesses complete elastic isotropy, characterized by a universal elastic anisotropy index of exactly zero. Elastic isotropy of this kind is rare among crystalline materials and means that the material’s stiffness is identical in every crystallographic direction. Because there are no weak planes or soft directions along which strain can localize, the inherent tendency of cyclic hydrogenation to open microscopic fissures is suppressed at its source. In practical terms, the crystal itself is structurally engineered by nature to flex uniformly as hydrogen enters and leaves the lattice, rather than shattering along preferential pathways. This combination of high ductility and perfect isotropy means the material can accommodate the volumetric changes of repeated hydrogenation cycles without accumulating the damage that has doomed many hydride candidates in real-world testing.

The methodology underpinning these conclusions reflects the current state of the art in computational materials science. The researchers performed full structural relaxations and finite-temperature ab initio molecular dynamics simulations using the generalized gradient approximation in its PBE parameterization, allowing the atoms to move according to quantum-mechanically calculated forces at realistic temperatures rather than being frozen into an idealized static lattice. Recognizing that standard approximations suffer from self-interaction errors that can distort predicted electronic properties, the team strictly refined the electronic structure calculations using the Heyd–Scuseria–Ernzerhof HSE06 hybrid functional, a more computationally expensive but significantly more accurate treatment of electron exchange. Radial distribution function analyses of the molecular dynamics trajectories then revealed how the atomic arrangement evolves as hydrogen is liberated, providing the kinetic evidence for the partial decomposition pathway that forms the study’s key novelty.

Context matters when weighing these results against the broader landscape of hydrogen storage research. Complex hydrides based on magnesium, boron, and aluminum have attracted decades of attention, but most suffer from sluggish kinetics, excessively high desorption temperatures, or irreversible decomposition that prevents efficient recharging. Perovskite-type hydrides of the general formula A2MH6 have emerged more recently as a chemically versatile family in which the choice of alkali metal and transition metal can be tuned to adjust storage capacity, stability, and release temperature. The new study positions K2NiH6 as a particularly favorable point within that compositional space, combining a low-lying desorption thermodynamics with the kinetic accessibility afforded by the partial decomposition route and the mechanical resilience conferred by its elastic properties. The work also builds on the authors’ prior computational explorations of related hexahydride and complex hydride systems, lending a methodological continuity that strengthens confidence in the predicted trends.

Naturally, important caveats remain. All of the reported findings are theoretical predictions derived from first-principles calculations, and while such simulations have an impressive track record of guiding experimental discovery, real materials invariably present complications that idealized models cannot fully capture, including defects, grain boundaries, impurity effects, surface passivation, and the slow degradation that can accompany thousands of operational cycles. Experimental synthesis and characterization of K2NiH6 under cycling conditions will be essential to confirm that the predicted near-ambient desorption kinetics and exceptional cyclic durability survive contact with laboratory and engineering realities. Questions of cost, scalability of synthesis, sensitivity to air and moisture, and the reversibility of the rehydrogenation step also await practical answers.

Nevertheless, the study represents a meaningful advance in the rational design of hydrogen storage materials. By identifying the specific partial decomposition reaction, quantifying the low diffusion barrier, and demonstrating intrinsic mechanical robustness, the researchers have provided a coherent mechanistic explanation for why K2NiH6 should perform well where other hydrides have struggled. As the global race to decarbonize transportation and energy storage accelerates, materials that can hold hydrogen densely and release it at room temperature without complex thermal management are exactly what the field needs. If subsequent experimental work validates these predictions, potassium hexahydronickelate could move from the pages of computational journals to the blueprint stage of next-generation hydrogen storage systems, bringing the vision of a practical hydrogen economy one substantial step closer to reality.

Subject of Research: Computational analysis of the solid-state hydrogen storage material potassium hexahydronickelate (K2NiH6)

Article Title: Unlocking the hydrogen storage potential of K2NiH6: high volumetric capacity and near-ambient dehydrogenation via partial decomposition

Article References: Yamçıçıer, S., & Yamçıçıer, Ç. (2026). Unlocking the hydrogen storage potential of K2NiH6: high volumetric capacity and near-ambient dehydrogenation via partial decomposition. Journal of Materials Science. https://doi.org/10.1007/s10853-026-13725-5

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13725-5

Keywords: hydrogen storage, K2NiH6, complex hydrides, dehydrogenation, density functional theory, ab initio molecular dynamics, solid-state hydrogen storage, perovskite hydride, volumetric capacity, elastic isotropy, DOE targets, clean energy materials

Röthlisberger, Professor of Computational Chemistry and Biochemistry at EPFL, has been recognized for pioneering contributions to ab initio molecular dynamics and quantum mechanical/molecular mechanical, or QM/MM, simulation methods. These approaches allow researchers to study chemical systems by combining highly accurate quantum-mechanical calculations with larger-scale molecular models. The result is a powerful computational framework for examining molecular reactions and materials whose complexity would be impossible to capture using a single modeling technique.

“I am deeply honored to receive this award, which bears the name of one of my long-time mentors and most inspiring role models,” Röthlisberger said. “To me, this distinction represents far more than personal recognition—it is a wonderful affirmation of the scientific contributions that I have been privileged to make, together with outstanding students, postdoctoral researchers, collaborators, and colleagues, throughout my career.”

Established by MDPI in 2025, the Michele Parrinello Award commemorates the scientific legacy of Professor Michele Parrinello, whose work transformed atomistic simulation and molecular dynamics. The award carries a prize of 50,000 euros and is intended to recognize researchers whose discoveries have produced lasting advances in computational science. Parrinello’s influence is particularly evident in methods that enable scientists to predict how atoms move, bonds form and break, and complex molecular structures change over time.

Röthlisberger’s research has helped extend these computational tools to problems spanning quantum chemistry, molecular biology, materials science, and sustainable energy. In QM/MM simulations, the chemically active region of a system—such as a reaction site, catalytic center, or biological active site—is treated using quantum mechanics, while the surrounding environment is represented with a less computationally demanding molecular-mechanics model. This multiscale strategy makes it possible to investigate realistic systems containing thousands of atoms without sacrificing a detailed description of the chemistry taking place at the center.

A major focus of her recent work has been the computational design and analysis of photovoltaic materials. Working with experimental researchers around the world, Röthlisberger has investigated the mechanisms governing dye-sensitized solar cells and perovskite solar cells. Her simulations have provided insight into how light is absorbed, how electrons and positive charge carriers move through a material, and how structural defects or chemical reactions can limit device performance. Such information can help researchers design solar cells that are more efficient, durable, and environmentally sustainable.

Perovskite solar cells have attracted intense scientific interest because they can be manufactured using relatively low-temperature processes and have achieved remarkable improvements in efficiency in a short period. However, their long-term stability and sensitivity to moisture, heat, light, and structural imperfections remain major challenges. Computational chemistry can reveal atomic-scale degradation pathways that are difficult to observe directly, allowing experimental teams to test targeted strategies for protecting the materials and extending their operating lifetimes.

Professor Xin-Gao Gong, chair of the Michele Parrinello Award Committee, described Röthlisberger as an exceptional leader in computational chemistry and molecular simulation. “Her innovative research has significantly advanced the predictive modeling of complex chemical and biological systems and has created lasting impact across multiple scientific disciplines,” Gong said. He added that her scientific achievements, commitment to education, and leadership in the international research community have contributed significantly to the development of modern computational science.

The award adds to Röthlisberger’s international distinctions. She is an elected Fellow of the American Association for the Advancement of Science, a member of the International Academy of Quantum Molecular Science, and a recipient of the Dirac Medal from the World Association of Theoretical and Computational Chemists and the Ruzicka Prize. Through the Michele Parrinello Award, MDPI is highlighting not only an individual career but also the growing role of simulation in solving urgent scientific problems. As computational methods become more accurate and increasingly connected to laboratory experiments, they are turning previously invisible molecular events into actionable knowledge for energy, biology, and materials innovation.

Subject of Research: Computational chemistry, molecular simulation, quantum mechanical/molecular mechanical methods, photovoltaic materials, and sustainable energy.

Web References: MDPI; Michele Parrinello Award

Image Credits: MDPI

Keywords

Ursula Röthlisberger, Michele Parrinello Award, MDPI, computational chemistry, molecular simulation, quantum chemistry, QM/MM, ab initio molecular dynamics, perovskite solar cells, dye-sensitized solar cells, photovoltaic materials, sustainable energy, materials science, EPFL