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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-Pressure Electrides: A Quantum Chemical Perspective

It has long been assumed that all matter will adopt simple close-packed lattices and become metallic under pressure, in accordance with the Thomas–Fermi–Dirac (TFD) model. However, this model struggles to explain pressure-driven complex structural transitions that have been observed in elements, including sodium, challenging our conventional understanding of compressed matter. Moreover, in stark contrast to the TFD model, first-principles calculations suggest that various elements and compounds become electrides under pressure. Electrides, characterized by concentrations of charge density at interstitial regions, can be thought of as ionic compounds where electrons behave as the anions. Though ambient-pressure molecular electrides have been extensively studied via experiments and computations, high-pressure electrides (HPEs) are not well-understood. The identification and characterization of HPEs have been, to date, based purely on theory, including topological analysis of the electron density and the electron localization function. Here, we review these theoretical analysis tools and suggest guidelines that can be used to classify systems as electrides. Moreover, we describe models used to rationalize the electronic structure of HPEs, drawing parallels with ambient-pressure molecular systems, and encourage the development of experimental techniques that provide evidence for the theoretically calculated charge localization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Strong Correlation DMRG and DFT

This project developed new ways to improve computer simulations of materials where electrons interact strongly with each other, a challenge for today’s most widely used method, density functional theory (DFT). We used an exact numerical method, the density matrix renormalization group (DMRG), to create highly accurate reference results for simple model systems, and used these to test DFT, prove when it will converge, and even train machine-learned functionals. We also invented new kinds of localized basis functions (“gausslets” and “multi-sliced gausslets”) and a “sliced-basis” approach that make high-accuracy simulations faster and more practical. These methods were applied to extended hydrogen systems, enabling the direct derivation of accurate low-energy models from first-principles calculations. We also introduced a new formalism, Conditional-Probability DFT, which could bypass traditional approximations. The tools and results from this work, including open-source software releases, will help scientists design and understand complex quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Catalytic, Spectroscopic, and Theoretical Studies of Fe 4 S 4 -Based Coordination Polymers as Heterogenous Coupled Proton–Electron Transfer Mediators for Electrocatalysis

Iron–sulfur clusters play essential roles in biological systems, and thus synthetic [Fe 4 S 4 ] clusters have been an area of active research. Recent studies have demonstrated that soluble [Fe 4 S 4 ] clusters can serve as net H atom transfer mediators, improving the activity and selectivity of a homogeneous Mn CO 2 reduction catalyst. Here, in this work, we demonstrate that incorporating these [Fe 4 S 4 ] clusters into a coordination polymer enables heterogeneous H atom transfer from an electrode surface to a Mn complex dissolved in solution. A previously reported solution-processable Fe 4 S 4 -based coordination polymer was successfully deposited on the surfaces of different electrodes. The coated electrodes serve as H atom transfer mediators to a soluble Mn CO 2 reduction catalyst displaying good product selectivity for formic acid. Furthermore, these electrodes are recyclable with a minimal decrease in activity after multiple catalytic cycles. The heterogenization of the mediator also enables the characterization of solution-phase and electrode surface species separately. Surface enhanced infrared absorption spectroscopy (SEIRAS) reveals spectroscopic signatures for an in situ generated active Mn–H species, providing a more complete mechanistic picture for this system. The active species, reaction mechanism, and the protonation sites on the [Fe 4 S 4 ] clusters were further confirmed by density functional theory calculations. The observed H atom transfer reactivity of these coordination polymer-coated electrodes motivates additional applications of this composite material in reductive H atom transfer electrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Atomic Orbital Energy Matching vs Overlap in Actinide-Ligand Dative Bonding

Prebonding conditions and dative bond formation in actinide(IV)hexachloride complexes with U, Np, and Pu are studied by density functional theory (DFT) calculations, focusing on the interplay of atomic orbital (AO) overlap and AO energy matching in the formation of molecular orbitals (MOs) and the subsequent identification of dative bonds. The extent of donation is tracked via population analysis, MO localization, and bond-order criteria. DFT Fock matrices are used to setup models in which varying numbers of valence AOs interact to form dative bonds. The results confirm, among other effects, a contribution to metal−ligand covalency from the actinide (An) 6p shell. Better matching of An(5f) and Cl(3p) energies occurs as the An(5f) level stabilizes with increasing An effective nuclear charge. A near-degeneracy occurs in the case of the α-spin orbitals of the Pu system, but it is inconsequential. Altogether, better AO energy matching for An(5f) and Cl(3p) along the series U, Np, Pu is counter-balanced by decreasing AO overlap and decreasing availability of 5f acceptor orbitals, leading to similar bond orders and extents of donation in the three systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Density functional theory-based surrogate kinetic models for heterogeneous reactions of hydrocarbon intermediates on silicon carbide

The increasing demand for high-performance materials in advanced technologies highlights the importance of achieving a fundamental understanding and potential control of silicon carbide (SiC) deposition processes. However, existing models often lack sufficient theoretical detail, relying heavily on empirical data and offering limited predictive capability. In particular, the complex surface chemistry governing SiC growth remains poorly understood. This study addresses these challenges by employing density functional theory (DFT) to investigate key heterogeneous reactions involving hydrocarbon intermediates on SiC surfaces, including dehydrogenation, hydrogenation, and carbon deposition. Transition state searches were conducted to identify reaction pathways and energy barriers. While first-principles calculations offer high accuracy, they are computationally intensive. To extend the utility of these first-principles results, vibrational analyses were performed using phonon-based statistical thermochemistry to compute temperature-dependent reaction rates which were used to develop Arrhenius-type surrogate kinetic models. Furthermore, the resulting framework provides a more rigorous, physically grounded basis for integrating atomistic insights into continuum-scale modeling, ultimately enabling improved prediction and optimization of SiC film growth in high-performance material systems.

Density Functional Theory↗
DOE OSTI2024

Fractional Statistics

The quantum-mechanical description of assemblies of particles whose motion is confined to two (or one) spatial dimensions offers many possibilities that are distinct from bosons and fermions. We call such particles anyons. The simplest anyons are parameterized by an angular phase parameter θ. θ = 0, π correspond to bosons and fermions, respectively; at intermediate values, we say that we have fractional statistics. In two dimensions, θ describes the phase acquired by the wave function as two anyons wind around one another counterclockwise. It generates a shift in the allowed values for the relative angular momentum. Composites of localized electric charge and magnetic flux associated with an abelian U(1) gauge group realize this behavior. More complex charge-flux constructions can involve nonabelian and product groups acting on a spectrum of allowed charges and fluxes, giving rise to nonabelian and mutual statistics. Interchanges of nonabelian anyons implement unitary transformations of the wave function within an emergent space of internal states. Anyons of all kinds are described by quantum field theories that include Chern–Simons terms. The crossings of one-dimensional anyons on a ring are unidirectional, such that a fractional phase θ acquired upon interchange gives rise to fractional shifts in the relative momenta between the anyons. The quasiparticle excitations of fractional quantum Hall states have long been predicted to include anyons. Recently, the anyon behavior predicted for quasiparticles in the ν = 1/3 fractional quantum Hall state has been observed in both scattering and interferometric experiments. Excitations within designed systems, notably including superconducting circuits, can exhibit anyon behavior. Such systems are being developed for possible use in quantum information processing.

Physics↗
DOE OSTI2025

A theoretical model for sheath dynamics in the two-plasma mode of a cylindrical filament discharge

We present a refined understanding of cylindrical plasma-facing emitter cathodes by examining the limitations of the conventional space charge limited model, which overlooks ion trapping dynamics within the virtual cathode. While conventional theory distinguishes between temperature-limited and space charge limited regimes based on electron current constraints, our findings reveal that trapped ions can form a quasi-neutral “second plasma,” expanding upstream and interacting with the primary plasma. In cylindrical and other non-planar geometries, an expanding trapped-ions layer produces current enhancement by converting more of the emitted electron flux to passing flux. The current enhancement leads to a complex coupling between the trapped-ions plasma and upstream plasma through ionizing collisions in the upstream region and charge exchange collisions in the virtual cathode. The coupling results in mutual density enhancement and at the same time, antagonistic expansion dynamics between the two plasma layers. The process is understood using a new “aid-compete” model. Numerical solutions, validated against simulations, reveal the model's capacity to predict system evolution and complex discharge behaviors, albeit with qualitative approximations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Synergistic Doping and Stabilization of Magnetically Tunable LnTi3(Sb,Sn)4 (Ln: Ce–Gd) Kagome Metals

Here, we present our synthesis and characterization of the LnTi3(Sb,Sn)4 (Ln: Ce, Pr, Nd, Sm, Gd) family of cleavable kagome metals. While these materials are isostructural to the LnTi3Bi4 family, they only form as (Sb,Sn) solid-solutions with no corresponding LnTi3Sb4 or LnTi3Sn4 phases. We use a combination of first-principles density functional theory (DFT) and crystal orbital Hamilton population (COHP) calculations to show that (Sb,Sn) alloying has a stabilizing effect on the structure by adjusting the Fermi level, filling bonding states, depopulating antibonding states, and adjusting the density of states (DOS) toward local minima, an effect we call “synergistic doping.” Through a detailed characterization of the SmTi3(Sb,Sn)4 series, we further demonstrate that the tunable Fermi level has a profound effect on the physical properties. We observe multiple magnetic phases that stem from a competition between antiferromagnetic (AFM) and ferromagnetic-like (FM) ground states. Furthermore, the (Sb,Sn) ratio allows us to tune from direct AFM-FM competition toward a complex admixture with properties reminiscent of the recently discovered TbTi3Bi4. Ultimately, our work demonstrates how the concept of synergistic doping provides a means to stabilize new structures while developing systems with intrinsically tunable chemical, magnetic, and electronic properties.

Ortiz, Brenden [ORNL] (ORCID:0000000213337003)↗
DOE OSTI2025

Ansatz-Free Hamiltonian Learning with Heisenberg-Limited Scaling

Learning the unknown interactions that govern a quantum system is crucial for quantum information processing, device benchmarking, and quantum sensing. The problem, known as Hamiltonian learning, is well understood under the assumption that interactions are local, but this assumption may not hold for arbitrary Hamiltonians. Previous methods all require high-order inverse polynomial dependency with precision, unable to surpass the standard quantum limit and reach the gold-standard Heisenberg-limited scaling. Whether Heisenberg-limited Hamiltonian learning is possible without prior assumptions about the interaction structures, a challenge we term ansatz-free Hamiltonian learning , remains an open question. In this work, we present a quantum algorithm to learn arbitrary sparse Hamiltonians without any structure constraints using only black-box queries of the system’s real-time evolution and minimal digital controls to attain Heisenberg-limited scaling in estimation error. Our method is also resilient to state-preparation-and-measurement errors, enhancing its practical feasibility. We numerically demonstrate our ansatz-free protocol for learning physical Hamiltonians and validating analog quantum simulations, benchmarking our performance against the state-of-the-art Heisenberg-limited learning approach. Moreover, we establish a fundamental trade-off between total evolution time and quantum control on learning arbitrary interactions, revealing the intrinsic interplay between controllability and total evolution-time complexity for any learning algorithm. These results pave the way for further exploration into Heisenberg-limited Hamiltonian learning in complex quantum systems under minimal assumptions, potentially enabling new benchmarking and verification protocols.

machine learning↗
DOE OSTI2025

Direct observation of key aluminum hydroxide prenucleation oligomers for gibbsite nucleation and crystallization in sodium aluminate solution by liquid ToF-SIMS

The mechanism of gibbsite (aluminum hydroxide) crystallization from highly alkaline solutions such as Bayer liquors remains poorly understood, where aluminum (Al) transforms from largely tetrahedrally coordinated aluminate monomers in sodium aluminate solutions into a network of octahedra in gibbsite crystals. A variety of traditional analytical approaches applied to this system do not readily reveal the presence of higher-order oligomeric intermediates. To overcome this limitation, we employed in-situ liquid Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) to examine the Al species present in concentrated sodium aluminate solutions favoring crystallization of gibbsite or sodium aluminate. A complex mixture of Al oligomers was found. By comparing the change in the relative concentration of Al oligomers with +1 and -1 charge, we were able to identify three major Al oligomer candidates, iso-tetramers, iso-pentamers, and cyclic-hexamers, for the nucleation and crystallization of gibbsite. The concentrations of iso-tetramers and iso-pentamers significantly surpass those of cyclic-hexamers. Time-dependent in-situ Raman spectroscopy analysis indicated that the appearance of gibbsite coincided with the peak concentration of these oligomers. The Density-functional theory (DFT) calculation suggests that the formation of iso-oligomers is more favorable than that of cyclic-hexamers. The combined results suggest that iso-tetramers and iso-pentamers play the most substantial role in the nucleation and growth of gibbsite in the sodium aluminate solutions. Our findings also suggest that the oligomers that promote gibbsite crystallization are more stable in dilute sodium aluminate solutions, making these solutions particularly suitable for efficient gibbsite crystallization. In conclusion, our study fills a major knowledge gap in understanding Al speciation that leads to the nucleation and crystallization of gibbsite in concentrated sodium aluminate solutions.

Bayer liquor↗
DOE OSTI2025

Operando probing dynamic migration of copper carbonyl during electrocatalytic CO2 reduction

Single crystals and shape-controlled nanocrystals are well known to exhibit facet-dependent catalytic properties. However, few studies have investigated how those nanocrystals evolve and (de)activate during reactions, calling for the development of nanoscale time-resolved operando methods. In this context, we have designed Cu nanocubes as a model system to elucidate the underlying driving force of dynamic nanocatalyst reconstruction during the CO2 reduction reaction (CO2RR). Operando electrochemical liquid-cell scanning transmission electron microscopy (EC-STEM) and synchrotron-based X-ray spectroscopy reveal the size- and potential-dependent complete transformation from (100)-oriented Cu@Cu2O nanocubes to polycrystalline metallic Cu nanograins under CO2RR conditions. In addition, machine learning-assisted operando four-dimensional STEM reveals that large Cu nanograins derived from nanocubes form mainly crystalline domains, while their smaller counterparts are more amorphous due to faster evolution kinetics. In situ Raman spectroscopy and density functional theory calculations suggest that CO drives the ejection of single Cu atoms, resulting in few-nanometre Cu clusters and the surface migration of highly mobile copper carbonyl (Cu–CO) species. Combined, these multimodal operando methods and theoretical approaches pave the way for understanding the complex structural evolution of energy-related nanocatalysts under electrochemical conditions.

Yang, Yao↗
DOE OSTI2025

Chlorocobaltate-Enabled Selective Separation of CoCl 2 from Mixed Chloride and Nitrate Salts of Mn, Co, and Ni

Described here is the effect of anionic metalates─chlorocobaltate and nitratocobaltate─on the heat-driven separation of the critical element cobalt from potentially competing transition metal salts. Resins bearing the hexadentate glycolamide receptor L (PS-L) exhibit sorption capacities, Q = 1.33 mmol/g for CoCl 2 and Q = 0.66 mmol/g for Co(NO 3 ) 2 , as inferred from sorption isotherm studies. This trend runs counter to the typical Hofmeister series for anion selectivity. Ion chromatographic analysis of a mixed CoCl 2 /Co(NO 3 ) 2 solution revealed an increase in chloride content from 55 mol % to 90 mol % after a single thermally driven catch-and-release cycle. This chloride-selective behavior was recapitulated in a mixed-metal cation, mixed-anion system containing the chloride and nitrate salts of Mn(II), Co(II), and Ni(II) at near-equimolar concentrations. PS-L also displayed enhanced selectivity for Co using this mixed stock solution as observed by ICP-OES. In contrast, for a nitrate-only solution containing Mn(II), Co(II), and Ni(II), PS-L showed increased affinity for Mn, with its proportion rising from 36.6 mol % to 58.1% after a single catch-and-release cycle. Density functional theory calculations support the suggestion that the enhanced uptake of Co(II) in chloride-rich media arises from the high thermodynamic stability of [CoCl 4 ] 2– , which facilitates its outer-sphere coordination to cationic resin-bound cobalt species. Single crystal X-ray crystallographic analyzes of L•MCl 2 (M = Mn, Co, Ni) and L•M(NO 3 ) 2 (M = Mn, Co) confirmed metal complexation by L in the solid state and the concomitant formation of metalate counteranions. Here, the present study highlights a relatively simple approach for separating cobalt from its transition metal congeners.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗
DOE OSTI2025

Correlated solvent coordinates accelerate multi-donor proton-coupled electron transfer

The rate of charge transfer within a discrete donor–acceptor (D/A) pair is well-described by semi-classical electron transfer theory, but the effects of multiple equivalent redox sites remain less understood. We report a series of ground-state intramolecular proton-coupled electron transfer (PCET) complexes designed to isolate the effects of donor number, N, while holding geometry, coupling, and driving forces constant. The [Ru(L) 3−N (OH) N ] 2+ complexes incorporate one, two, or three identical phenolic electron donors linked to Ru through rigid phenanthroline bridges (OH = 2,4-di-tert-butyl-6-(1-methyl-1H-imidazo[4,5-f][1,10]phenanthrolin-2-yl)phenol). Upon flash photolysis and oxidative quenching with methyl viologen (MV 2+ ), the transient Ru(III) oxidizes an appended phenol by PCET with the hydrogen-bonded imidazole nitrogen atom functioning as the base. The rate increased by 3.4-fold and 5.7-fold (1.7-fold and 1.9-fold after statistical correction) for two- and three-donor complexes compared to the single-donor system. The supra-statistical acceleration is attributed to a reduced effective outer sphere reorganization energy (λ m ) modeled by a partially shared solvent reaction coordinate, in which a subset of solvent dipoles is already oriented to stabilize charge from any donor. The final phenoxyl radical state is localized due to the transfer of a proton, and the recombination reaction with the viologen radical is not accelerated. These results demonstrate the effects of solvent dynamics on intramolecular PCET rates, offering a new strategy for the design of synthetic charge transfer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗
DOE OSTI2025

Strongly nonlinear wave propagation in elasto-plastic metamaterials: Low-order dynamic modeling

Nonlinear elastic metamaterials are known to support a variety of dynamic phenomena that enhance our capacity to manipulate elastic waves. Since these properties stem from complex, subwavelength geometry, full-scale dynamic simulations are often prohibitively expensive at scales of interest. Prior studies have therefore utilized low-order effective medium models, such as discrete mass-spring lattices, to capture essential properties in the long-wavelength limit. While models of this type have been successfully implemented for a wide variety of nonlinear elastic systems, they have predominantly considered dynamics depending only on the instantaneous kinematics of the lattice, neglecting history-dependent effects, such as wear and plasticity. Here, to address this limitation, the present study develops a lattice-based modeling framework for nonlinear elastic metamaterials undergoing plastic deformation. Due to the history- and rate-dependent nature of plasticity, the framework generally yields a system of differential-algebraic equations whose computational cost is significantly greater than an elastic system of comparable size. We demonstrate the method using several models inspired by classical lattice dynamics and continuum plasticity theory and explore means to obtain empirical plasticity models for general geometries, thereby gaining insight into the influence of microstructural plasticity on effective material performance, which can be used to improve the design of nonlinear mechanical metamaterials.

Dynamic simulation↗
DOE OSTI2026

Machine learning-based interatomic potential development and phase transition analysis of ferroelectric hafnium dioxide

The ferroelectric phase (𝑃⁢𝑐⁢𝑎⁢2 1 , which is in orthorhombic symmetry) of hafnium dioxide (HfO 2 ) has gained much attention due to its potential applications in nanoelectronics and advanced memory devices. However, its complex phase behavior under external stimuli, such as pressure and temperature, remains a subject of intense investigation. This study focuses on developing a machine learning-based interatomic potential (MLIP) that is trained with data from density-functional theory (DFT) calculations to simulate phase transitions and mechanical properties of HfO 2 . The developed MLIP predicts lattice parameters, equations of state, bulk and shear moduli, and elastic constants that closely align with DFT predictions for several phases and at various pressures. Once validated, the MLIP is used to investigate the phase transitions of ferroelectric HfO 2 (𝑃⁢𝑐⁢𝑎⁢2 1 ) under both isobaric and constant stress conditions at elevated temperatures ranging from 200 to 2500 K. We used several complementary methods, including local symmetry identification, radial distribution function, and x-ray diffraction characterization, to identify interesting phase transitions among several competitive hafnia phases predicted from our simulations. The suggested methods uniformly reveal that under pure deviatoric condition, the system favors a transition from the orthorhombic 𝑃⁢𝑐⁢𝑎⁢2 1 phase to a tetragonal (𝑃⁢4 2 /𝑛⁢𝑚⁢𝑐) phase, whereas a zero stress condition drives the system from the 𝑃⁢𝑐⁢𝑎⁢2 1 phase to another orthorhombic (𝑃⁢𝑏⁢𝑐⁢𝑛) phase. These findings provide crucial insights into stress and temperature-induced phase behavior of hafnia, guiding future experimental and theoretical studies for optimizing hafnia-based ferroelectric devices.

Ferroelectric HfO2↗
DOE OSTI2025

Achieving the hydrogen shot: Interrogating ionomer interfaces

The aim of this study is to enable the hydrogen economy and decarbonize various sectors in our environment that requires less expensive and more durable water electrolyzers, which can meet the Hydrogen-Shot target. The key is to improve the ionomer interfaces in low-temperature water electrolyzers as rapidly as possible, but to do so, it requires a systematic and holistic campaign combining both experiments and theory. In this perspective, we discuss the issues of electrolyzers and needs for translational science. We then present the approach that the Energy EarthShot Research Center: Center for Ionomer-based Water Electrolysis is taking in hopes of inspiring the community with this approach that can be leveraged to multiple problems and technologies.Graphical abstractHighlightsOne way to achieve the Hydrogen-Shot goal of low-cost, clean hydrogen, is advancing research and development on the interfaces of water electrolyzers for both performance and lifetime. The Center for Ionomer-based Water Electrolysis is exploring new techniques and strategies to not only interrogate interfacial phenomena in water electrolyzers to increase efficiency and durability, but also a new paradigm related to synergistic, cojoined experimental and theoretical research.DiscussionCatalyst\ionomer interfaces are complex and not fully understood, but through investigating different interfaces and utilizing digital and physical twins, we can elucidate key mechanisms and understanding.Understanding the dynamic double layer in electrochemical systems that use solid electrolytes is crucial to identifying and mitigating the controlling phenomena to enable increased performance and durability at the technology level.Studying the time and length scales of interfacial changes can be a powerful tool to understand reaction mechanisms and changes in the electrolyzer performance and durability.

Fornaciari, Julie C↗