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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Understanding the selectivity of nonsteroidal anti-inflammatory drugs for cyclooxygenases using quantum crystallography and electrostatic interaction energy

Quantum crystallography methods have been employed to investigate complex formation between nonsteroidal anti-inflammatory drugs (NSAIDs) and cyclooxygenase (COX) enzymes, with particular focus on the COX-1 and COX-2 isoforms. This study analyzed the electrostatic interaction energies of selected NSAIDs (flurbiprofen, ibuprofen, meloxicam and celecoxib) with the active sites of COX-1 and COX-2, revealing significant differences in binding profiles. Flurbiprofen exhibited the strongest interactions with both COX-1 and COX-2, indicating its potent binding affinity. Celecoxib and meloxicam showed a preference for COX-2, consistent with their known selectivity for this isoform, while ibuprofen showed comparable interaction energies with both isoforms, reflecting its nonselective inhibition pattern. Key amino-acid residues, including Arg120, Arg/His513 and Tyr355, were identified as critical determinants of NSAID selectivity and binding affinity. The findings highlight the complex interplay between interaction energy and selectivity, suggesting that while electrostatic interactions play a fundamental role, additional factors such as enzyme dynamics and the hydrophobic effect also contribute to the therapeutic efficacy and safety profiles of NSAIDs. These insights provide valuable guidance for the rational design of NSAIDs with enhanced therapeutic benefits and minimized adverse effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

pyDiSCaMB : enabling the use of multipolar scattering factors in Phenix

Multipolar scattering models, such as the transferable aspherical atom model, account for atomic chemical interactions and provide a more accurate representation of experimental data. However, the simpler independent atom model (IAM), which assumes non-interacting atoms, is the only model available in the most widely used macromolecular refinement programs. This is primarily because IAM offers a hard-to-beat combination of computational efficiency and modelling power at typical macromolecular resolutions. By contrast, more accurate multipolar modelling has historically been limited due to its computational cost and the absence of an interface between software capable of calculating structure factors and gradients based on multipolar models and software designed for macromolecular refinement. This work introduces pyDiSCaMB , a Python software package designed to integrate between the computational crystallography toolbox ( cctbx ) and the quantum crystallography library DiSCaMB ( Densities in Structural Chemistry and Molecular Biology ), thus enabling multipolar scattering models in Phenix 's toolkit. The implementation, features and capabilities of pyDiSCaMB are presented, the runtimes for the calculation of structure factor and target gradients with respect to atomic parameters are explored, and Fourier images of electrostatic potential, electron density and deformation maps are computed as illustrative examples. The pyDiSCaMB library will make multipolar modelling widely available to the structural biology community, potentially transforming refinement and model-building for both crystallography and cryogenic electron microscopy (cryoEM).

MATTS data bank↗
DOE OSTI2025

Comparative Study of Solvatomorphs of Stryker's Reagent Using MicroED and Quantum Mechanics

Abstract The atomic position of hydrogen atoms in metal hydrides has been a long‐standing structural question in inorganic chemistry given that hydride delivery is integral to diverse chemical reactions. Microcrystal electron diffraction (microED), with it's increased sensitivity toward hydrogen atoms relative to X‐ray diffraction, offers a potential path to addressing this challenge. Herein, the first microED study of Stryker's reagent is reported, resulting in the structure of a new benzene solvate. Improved accuracy for hydrogen atom positions was obtained via a quantum crystallography (QCr) approach, Hirshfeld atom refinement (HAR). Structural and topological analysis supports edge bridging hydrides in the microED structure of a THF solvate form, consistent with previous diffraction studies. Interestingly, analysis of a new benzene solvate, discovered in this study, is consistent with mixed edge‐ and face‐bridging hydrides.

Jha, Kunal K. [Division of Chemistry &amp, Chemica↗
DOE OSTI2026

Hydride and Seek: Comparing Crystallographic Hydride Placement Techniques with an Open-Shell Cobalt Complex

Locating hydrides is crucial in organometallic chemistry but difficult to do accurately using X-ray diffraction. Electron diffraction has been proposed as a way to overcome this problem but has not been systematically compared to neutron diffraction and to quantum crystallography (Hirshfeld atom refinement, HAR) to test this hypothesis. Here, we present a comparative analysis of methods for a terminal cobalt hydride complex by comparing a single-crystal neutron diffraction reference structure to results from single-crystal X-ray diffraction with and without Hirshfeld atom refinement (HAR, NoSpherA2), density functional theory (DFT), and electron diffraction (3D-ED/MicroED) refined under kinematical and dynamical formalisms. Conventional X-ray diffraction gives lower precision than neutron diffraction as expected. Despite expected improvements, HAR gives systematic deviation from the neutron benchmark. Interestingly, optimized DFT equilibrium geometries are closer to the neutron value than the value from HAR. On the other hand, electron diffraction with a high-quality data set coupled with dynamical refinement localizes the hydride in difference maps and gives excellent agreement with the neutron data. Dynamical refinement is crucial, as kinematical refinement does not allow assignment of a hydride peak. This cross-modal comparison defines the conditions under which 3D-ED/MicroED delivers high-precision metal–hydride distances for this open-shell cobalt hydride.

anions↗
DOE OSTI2025

Combining Reactive Quantum-Mechanical Molecular-Dynamics Simulations with Mutagenesis, Crystallography, and Enzyme Kinetics to Reveal Plausible Steps of Isocyanide Hydratase Catalysis

A complete understanding of enzyme mechanisms requires atomistic details of chemical reactions. Quantum-based molecular dynamics simulations (QMD) are a potential source of this information, but trade-offs between accuracy and computational cost have limited their use. We previously developed extended Lagrangian Born–Oppenheimer molecular dynamics (XL-BOMD) methods that leverage a negligible compromise in accuracy to substantially decrease the cost of QMD simulations. Here, we develop a reactive QMD approach using the latest XL-BOMD formulation, which enables efficient simulations of highly reactive systems, and use it to investigate mechanisms of intermediate formation in isocyanide hydratase (ICH) catalysis. In QMD simulations, molecular analogs of ICH active site residues reacted with para-nitrophenyl isocyanide, forming a thioimidate. Analysis of simulated atomic configurational and charge dynamics revealed a pathway where protonation of the isocyanide carbon occurs prior to thioimidate formation and suggested a possible role of Asp17 as a proton donor in the early phase of ICH catalysis. To test whether the pathway seen using the reactive QMD approach might be relevant to ICH catalysis, we performed X-ray crystallography and pre-steady-state enzyme kinetics studies of wild-type and D17N mutant ICH. Both the structure and kinetics are sensitive to the D17N mutation in a manner that is consistent with the order of the reaction steps seen in the simulations. Mobile protons play essential roles in many enzymes, yet they are difficult to observe experimentally, making the ordering of proton-dependent steps ambiguous in many enzyme mechanisms. The ability to directly simulate model reactions for the design of experiments that provide information about enzyme mechanisms involving mobile protons demonstrates the significance of our reactive QMD approach and motivates further biological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

In Crystallo Synthesis of a Triplet Silver Nitrene

Reactive silver nitrenes are proposed intermediates in Ag-catalyzed C–H amination and olefin aziridination reactions. Synthesis and characterization of reactive Ag nitrenes has proven elusive due to fleeting lifetimes and argentophilic aggregation of Ag(I) precursors in solution. Here, we report the templated in crystallo synthesis and characterization of a mononuclear Ag nitrene supported by a tris(pyrazolyl)borate ligand. Photolytic N 2 elimination from the corresponding aryl azide complex yields a structurally defined Ag nitrene with a triplet ground state, as confirmed by crystallography, magnetic measurements, and quantum chemical calculations. This species displays both stoichiometric and catalytic nitrene transfer reactivity, enabling carbazole and indole formation from organic azides. These results leverage in crystallo templating to isolate a mononuclear triplet nitrene of Ag and provide a platform to experimentally elucidate ligand-controlled selectivity in Ag-catalyzed nitrene transfer catalysis.

Azides↗
DOE OSTI2024

Ligand‐Mediated Quantum Yield Enhancement in 1‐D Silver Organothiolate Metal–Organic Chalcogenolates

X-ray free electron laser (XFEL) microcrystallography and synchrotron single-crystal crystallography are used to evaluate the role of organic substituent position on the optoelectronic properties of metal–organic chalcogenolates (MOChas). MOChas are crystalline 1D and 2D semiconducting hybrid materials that have varying optoelectronic properties depending on composition, topology, and structure. While MOChas have attracted much interest, small crystal sizes impede routine crystal structure determination. A series of constitutional isomers where the aryl thiol is functionalized by either methoxy or methyl ester are solved by small molecule serial femtosecond X-ray crystallography (smSFX) and single crystal rotational crystallography. While all the methoxy examples have a low quantum yield (0-1%), the methyl ester in the ortho position yields a high quantum yield of 22%. Here, the proximity of the oxygen atoms to the silver inorganic core correlates to a considerable enhancement of quantum yield. Four crystal structures are solved at a resolution range of 0.8–1.0 Å revealing a collapse of the 2D topology for functional groups in the 2- and 3- positions, resulting in needle-like crystals. Further analysis using density functional theory (DFT) and many-body perturbation theory (MBPT) enables the exploration of complex excitonic phenomena within easily prepared material systems.

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

AQuaRef: machine learning accelerated quantum refinement of protein structures

Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library-based stereochemical data, which, in addition to being limited to known chemical entities, do not include meaningful noncovalent interactions. Quantum mechanical (QM) calculations could alleviate these issues but are too expensive for large molecules. Here we present a novel AI-enabled Quantum Refinement (AQuaRef) based on AIMNet2 machine learned interatomic potential (MLIP) mimicking QM at substantially lower computational costs. By refining 41 cryo-EM and 30 X-ray structures, we show that this approach yields atomic models with superior geometric quality compared to standard techniques, while maintaining an equal or better fit to experimental data. Notably, AQuaRef aids in determining proton positions, as illustrated in the challenging case of short hydrogen bonds in the parkinsonism-associated human protein DJ-1 and its bacterial homolog YajL.

Zubatyuk, Roman [Carnegie Mellon University, Pitts↗
DOE OSTI2026

Environmental Contributions to Proton Sharing in Protein Low-Barrier Hydrogen Bonds

Hydrogen bonds (H-bonds) are central to biomolecular structure and dynamics. Although H-bonds are typically characterized by well-defined proton positions, proton delocalization has been proposed to play a role in facilitating enzyme catalysis and allostery in some systems. Experimentally locating protons is difficult, hampering the study of proton mobility in H-bonds. We used neutron crystallography, atomic resolution X-ray bond length analysis, and large quantum mechanics/molecular mechanics-Born–Oppenheimer molecular dynamics (QM/MM-BOMD) simulations to comprehensively characterize the shared proton/deuteron in a Glu–Asp low-barrier hydrogen bond (LBHB) in the bacterial protein YajL that is a conventional H-bond in the homologous disease-associated human protein DJ-1. X-ray bond length analysis of protiated and perdeuterated DJ-1 and YajL shows no significant effect of deuteron substitution on these carboxylic acid-carboxylate H-bonds but does reveal an effect at the active site glutamic acid near a cysteine thiolate. Residues in an H-bonded network that might favor LBHB formation in YajL were interrogated by the mutation of homologous residues in DJ-1. A distal DJ-1 substitution increases proton delocalization in the Glu–Asp H-bond, demonstrating that mutations within extended H-bond networks can modulate proton transfer barriers in carboxylic acid-carboxylate H-bonds. In addition, proton mobility in the H-bond is correlated with dimer-spanning motions in the QM/MM-BOMD simulations of YajL and DJ-1. Our results show that proton delocalization can be tuned using combined bioinformatic, structural, and computational information, opening the possibility of using engineered proton delocalization as a probe of H-bonding environments and as a tool to test hypotheses about LBHB function.

Lin, Jiusheng [University of Nebraska, Lincoln, NE↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Au 76 (SC 6 H 4 - p -CH 3 ) 42 Square Quantum Platelet: One-Dimensional Growth of Quantum Rods Turns 90 Degrees

The growth pattern of atomically precise nanoclusters (NCs) is of fundamental interest, and the structural effect on their photoluminescence (PL) is important owing to their PL in the second near-infrared (NIR-II) range (900–1700 nm optoelectronically or 1000–1700 nm biologically) that holds great promise for optoelectronic and biomedical applications. Because of the small energy gaps required for NIR-II emission, the PL performance of NIR-II luminophores is largely limited by nonradiative processes. In this work, we discovered a Au 76 (p-MBT) 42 (Au 76 ) (p-MBTH = p-methylbenzenethiol) nanocluster featuring a face-centered cubic (fcc) core in a square shape (edge length: 1 nm). This square quantum platelet can be viewed as a side-facet (010) growth of the Au 52 (p-MBT) 32 (Au 52 ) rod, as opposed to the (001) facet growth. We found that Au 76 exhibits bright emission centered at 970 nm with a PL quantum yield (PLQY) of 30% in solution under ambient conditions, which can be further enhanced to 40% when the solution is deaerated. X-ray crystallography analysis coupled with time-resolved spectroscopy revealed that the nearly doubled PLQY compared to Au 52 (18.3%) was resulted from shorter Au–Au bond lengths in Au 76 (average 2.835 Å) than that in Au 52 (3.04 Å). This work provides important insights into the design of highly luminescent NCs, which are promising for photovoltaics, photocatalysis, and optoelectronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Synthesis and Characterization of [Ni(H 2 O)(7-P Ph 2 N ArSO3 ) 2 ](NaBF 4 ) for Light-Driven Quantum Dot-Catalyst Hydrogen Evolution

Light-driven hydrogen generation from water is a route to carbon-neutral fuels. However, the integrated light absorbers and catalysts must be compatible and functional under the same conditions. A sulfate-functionalized complex, [Ni(H 2 O)(7-P Ph 2 N ArSO3 ) 2 ](NaBF 4 ), where P Ph 2 N ArSO3 = 4-(3,6-diphenyl-1,3,6-azadiphosphepan-1-yl)benzenesulfonate), was synthesized and characterized. A solid-state structure from single-crystal X-ray crystallography is also reported. The electrocatalytic activity for hydrogen evolution of this complex in 7:3 H 2 O:CH 3 CN was characterized by cyclic voltammetry and controlled potential electrolysis, with a maximum observed rate of 83 s –1 . Density functional theory was used to characterize the favorable binding of the sulfate functionalities to cadmium sulfide quantum dots. Experimental assembly of these catalysts onto cadmium sulfide quantum dots was successful. In conclusion, both fast electron transfer and light-driven pH-dependent hydrogen evolution were observed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Upper critical magnetic field and multiband superconductivity in artificial high-𝑇 𝑐 superlattices of nano quantum wells

Artificial high-T c superlattices (AHTS) composed of quantum building blocks with tunable superconducting critical temperature have been synthesized by engineering their nanoscale geometry using the Bianconi-Perali Valletta (BPV) two-gap superconductivity theory. These quantum heterostructures consist of quantum wells made of superconducting, modulation-doped Mott insulators (S), confined by a metallic (N) potential barrier. The lattice geometry has been carefully engineered to induce the predicted Fano-Feshbach shape resonance between the gaps, near a topological Lifshitz transition. Here, we validate the BPV theory by providing compelling experimental evidence that AHTS samples, at the peak of the superconducting dome, exhibit resonant two-band, two-gap superconductivity. This is demonstrated by measuring the temperature dependence of the upper critical magnetic field, μ 0 H c2 , in samples with superlattice periods 3.3 < d < 5.28 nm and L/d ratios close to the magic value 2/3 (where L is the thickness of the superconducting La 2 CuO 4 layer and d is the superlattice period). Here, the data reveal the predicted upward concavity in H c2 (T) and a characteristic kink in the coherence length as a function of temperature, confirming the predicted two-band superconductivity with Fermi velocity ratio ≈ 0.25 and significant pair-exchange term among the two condensates.

Heterostructures↗
DOE OSTI2025

Investigating the universality of five-point QCD scattering amplitudes at high energy

We investigate 2 → 3 QCD scattering amplitudes in multi-Regge kinematics, i.e. where the final partons are strongly ordered in rapidity. In this regime amplitudes exhibit intriguing factorisation properties which can be understood in terms of effective degrees of freedom called reggeons. Working within the Balitsky/JIMWLK framework, we predict these amplitudes for the first time to next-to-next-to-leading logarithmic order, and compare against the limit of QCD scattering amplitudes in full colour and kinematics. We find that the latter can be described in terms of universal objects, and that the apparent non-universality arising at NNLL comes from well-defined and under-control contributions that we can predict. Thanks to this observation, we extract for the first time the universal vertex that controls the emission of the central-rapidity gluon, both in QCD and $\mathcal{N}$ = 4 super Yang-Mills.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Can ferric-oxyl excited states explain elongated iron-oxygen bonds in heme peroxidase catalytic intermediates?

The use of X-ray structures to determine and interpret the ferryl iron-oxygen bond order in molecular oxygen-activating heme enzymes has, in the past, been controversial. This has mainly stemmed from the susceptibility of ferryl species to X-ray-induced electronic state changes. In this work we establishe using time-resolved serial femtosecond X-ray crystallography (tr-SFX) on a dye-decolourising peroxidase that the ferryl intermediate species (Compounds I and II) captured following in situ mixing of microcrystals with H 2 O 2 have single, rather than the double bond character expected. X-ray emission validated tr-SFX data with quantum refinement, time-dependent-DFT calculations and QM/MM geometry optimizations together support the concept that the single iron-oxygen bond character is not an indication of ferryl reduction or a protonated form (Fe IV -OH) but is instead attributed to the existence of accessible excited states possessing ferric-oxyl (Fe III –O •– ) character. Such states offer insight into the nature of ferryl heme.

Williams, Lewis J. [University of Essex, Colcheste↗
DOE OSTI2026

Validated ligand geometries for macromolecular refinement restraints and molecular-mechanics force fields

In macromolecular structure refinement, the low observation-to-parameter ratio and the lack of high-resolution data are countered by using a priori information in the form of restraints. Having accurate geometries of the chemical entities in the sample is paramount for generating accurate chemical restraints and, therefore, accurate macromolecular structures. In particular, it is desirable to have accurate restraints for known and novel ligand entities. Quantum mechanics (QM) can minimize the energy of a ligand by adjusting its geometry, and these geometries can be used to generate restraints for macromolecular refinement. This article describes a library of approximately 37 000 small molecules extracted from the Chemical Component Dictionary in the Protein Data Bank and minimized by density-functional QM. The library includes restraint files for use in crystallography or cryo-EM refinement, along with files suitable for molecular-dynamics simulation. Because the geometries are validated using the Cambridge Structural Database, the restraints library provides users with both functional restraints and minimized geometries. This work also provides procedures for generating new and accurate restraints.

Amber↗
DOE OSTI2026

Mechanism of Tyrosine-Driven Deprotonation in Photosystem II Revealed by Multiscale Simulations

Photosystem II (PSII) drives light-induced water oxidation via stepwise redox transitions of its oxygen-evolving complex (OEC), a Mn 4 Ca cluster advancing through five intermediate S-states (S 0 –S 4 ). The S 2 → S 3 transition involves a redox event in which a Mn ion donates an electron to the redox-active tyrosine YZ, coupled to deprotonation of an OEC-bound water ligand─yet the underlying coupling mechanism remains unresolved. Time-resolved serial femtosecond crystallography (TR-SFX) has revealed transient electron density shifts near the redox-active tyrosine Y Z , interpreted as sequential oxidation and reduction, with reduction initiating ∼1 μs after excitation and substantially progressed by 30 μs. However, this interpretation conflicts with kinetics from photothermal beam deflection (PBD), time-resolved X-ray absorption spectroscopy (TR-XAS), and electron paramagnetic resonance (EPR), which place electron transfer at 190–400 μs and proton transfer around 30 μs. Here, we reconcile these discrepancies using quantum mechanics/molecular mechanics (QM/MM) and molecular dynamics (MD) simulations. We show that oxidation of P680 and Y Z breaks the symmetry of the nearby hydrogen bonds involving water molecule W4, displacing Y Z and replicating the TR-SFX features of Y Z and Q165 observed at 1 μs. This local perturbation propagates through a hydrogen-bond network, transmitting the electrostatic signal from Y Z to the E65-E312 dyad and triggering redox-coupled deprotonation via the Cl1 channel. By 30 μs, the hydrogen-bond symmetry is restored through deprotonation of W2 (or alternatively W1), reproducing the disappearance of TR-SFX density differences around Y Z and Q165 without requiring Y Z reduction. Our proposed mechanism also gives molecular insights into the O6* density, assigning it to water reorganization rather than a discrete Ca-bound hydroxide species. Here, our results reveal a detailed atomistic mechanism linking Y Z oxidation to long-range proton release and suggest a functional role for the nearby Cl – ion in proton transfer. More broadly, this study underscores the importance of hydrogen-bond dynamics in mediating redox-driven proton transport and demonstrates how integrative simulations can resolve mechanistic ambiguities.

Deprotonation↗
DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗