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At least 343 records · Page 19

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DOE OSTI2026

Transcriptomic and functional analyses uncover a conserved effector driving genotype-dependent virulence in the Sphaerulina musiva-Populus trichocarpa interaction

The introduction of invasive microbes compromises the structure, biodiversity, and function of naïve ecosystems. Sphaerulina musiva, a hemibiotrophic pathogen that causes leaf spot and stem cankers in Populus species, exemplifies an invasive fungal pathogen spread by human activities. However, the genetic mechanisms of pathogenicity and virulence are poorly understood, impeding mitigation strategies. We utilized RNA sequencing to identify fungal effectors linked to stem canker formation, informing the development of future strategies for effective disease management. Our analysis revealed 70 genes differentially expressed at 2 weeks and 110 genes at 3 weeks between inoculated trees and controls. Notably, the gene with the highest expression at 2 weeks and the second highest at 3 weeks was homologous to Extracellular protein 2 (Ecp2). Complementary genome-wide association studies linked sequence polymorphisms in this locus to phenotypic variation in disease severity. Infiltration of S. musiva Ecp2 into Populus trichocarpa leaves induced necrosis in susceptible genotypes. Gene disruption using a CRISPR-Cas9 RNP system resulted in a genotype-dependent reduction of stem canker and disease severity. Tracing the evolutionary history of this effector across the fungal kingdom, we uncovered clade-specific gene-family expansions and orthologs in new species. These findings raise questions about the function and adaptive significance of these gene families in fungal lifestyles. Our study provides the first tractable target for breeding resistant poplar genotypes, addressing the challenges of managing S. musiva and uncovering mechanisms that drive its virulence, and provides deeper insights into the evolutionary dynamics of a conserved small-secreted protein with a diversity of functions.

Sondreli, Kelsey L [Oregon State University]↗

DOE OSTI2026

From Spin to Pseudospin Symmetry: The Origin of Magic Numbers in Nuclear Structure

Magic numbers lie at the heart of nuclear structure, reflecting enhanced stability in nuclei with closed shells. While the emergence of magic numbers beyond 20 is commonly attributed to strong spin-orbit coupling, the microscopic origin of the spin-orbit potential remains elusive, owing to its dependence on the resolution scale and renormalization scheme of nuclear forces. Here, we investigate the evolution of nuclear shell structure with varying momentum resolution in nuclear interactions derived from chiral effective field theory, using the similarity renormalization group to link different scales. We uncover a novel transition from spin symmetry to pseudospin symmetry as the resolution scale decreases, during which magic numbers emerge naturally. A similar pattern is found in calculations using relativistic one-boson-exchange potentials, underscoring the robustness of the phenomenon. This establishes a direct connection between realistic nuclear forces with a high resolution scale and effective nuclear forces at coarse-grained scales, offering a first-principles explanation for the origin of magic numbers and pseudospin symmetry in nuclear shell structure and new insights into the structure of exotic nuclei far from stability

Energy levels↗

DOE OSTI2025

Isoreticular Tolerance and Phase Selection in the Synthesis of Multi‐Module Metal–Organic Frameworks for Gas Separation and Electrocatalytic OER

Abstract Although metal–organic frameworks are coordination‐driven assemblies, the structural prediction and design using metal‐ligand interactions can be unreliable due to other competing interactions. Leveraging non‐coordination interactions to develop porous assemblies could enable new materials and applications. Here, we use a multi‐module MOF system to explore important and pervasive impact of ligand‐ligand interactions on metal‐ligand as well as ligand‐ligand co‐assembly process. It is found that ligand‐ligand interactions play critical roles on the scope or breakdown of isoreticular chemistry. With cooperative di‐ and tri‐topic ligands, a family of Ni‐MOFs has been synthesized in various structure types including partitioned MIL‐88‐acs ( pacs ), interrupted pacs (i‐ pacs ), and UMCM‐1‐muo. A new type of isoreticular chemistry on the muo platform is established between two drastically different chemical systems. The gas sorption and electrocatalytic studies were performed that reveal excellent performance such as high C 2 H 2 /CO 2 selectivity of 21.8 and high C 2 H 2 uptake capacity of 114.5 cm 3 /g at 298 K and 1 bar.

Xiao, Yuchen [Department of Chemistry University o↗

DOE OSTI2025

Isoreticular Tolerance and Phase Selection in the Synthesis of Multi‐Module Metal–Organic Frameworks for Gas Separation and Electrocatalytic OER

Xiao, Yuchen [Department of Chemistry University o↗

DOE OSTI2026

Bound states of Ω baryons in light nuclei

Here, we investigate bound states of light Ω 3⁢𝑥 clusters (𝑥=𝑠,𝑐), motivated by the Ω 3⁢𝑠 ⁢𝑁 potential recently developed by the HAL QCD collaboration. To regularize this potential, we remove the deeply attractive core at 𝑟 < 0.4 fm and parametrize the long-range component (𝑟 > 0.4 fm) using a two-range Gaussian form. This procedure preserves the relevant two-body bound-state energy while having a negligible effect on the Ω 3⁢𝑠⁢ 𝑁⁢𝑁 and Ω 3⁢𝑠⁢ Ω 3⁢𝑠 ⁢𝑁 systems. An effective Ω 3⁢𝑠 ⁢𝛼 potential is then constructed by fitting a two-range Gaussian function to the long-range component of the folding potential, enabling calculations of the bound-state energies of the Ω 3⁢𝑠⁢ 𝛼, Ω 3⁢𝑠⁢ 𝛼⁢𝛼, and Ω 3⁢𝑠 ⁢Ω 3⁢𝑠 ⁢𝛼 systems. The regularization procedure leads to a substantial reduction in bound-state energies compared to those obtained with the original potential. We further extend the analysis to Ω 3⁢𝑐 -cluster systems by introducing an Ω 3⁢𝑐 ⁢𝑁 interaction, derived by comparing the existing Ω 3⁢𝑠⁢ Ω 3⁢𝑠 and Ω 3⁢𝑐 ⁢Ω 3⁢𝑐 potentials. Our results suggest that several parametrizations predict bound states in Ω 3⁢𝑐 -containing clusters. Finally, the Ω 3⁢𝑠 ⁢Ω 3⁢𝑠 interaction is described using a contactlike potential approach, motivated by the effective field theory.

binding energy & masses↗

DOE OSTI2025

Dilute Paramagnetism and Non-Trivial Topology in Quasicrystal Approximant Fe4Al13

A very fundamental property of both weakly and strongly interacting materials is the nature of their magnetic response. In this work, we detail the growth of crystals of the quasicrystal approximant Fe4Al13 with an Al flux solvent method. We characterize our samples using electrical transport and heat capacity, yielding results consistent with a simple non-magnetic metal. However, magnetization measurements portray an extremely unusual response for a dilute paramagnet and do not exhibit the characteristic Curie behavior expected for a weakly interacting material at high temperature. Electronic structure calculations confirm metallic behavior but also indicate that each isolated band near the Fermi energy hosts non-trivial topologies, including strong, weak, and nodal components, with resultant topological surface states distinguishable from bulk states on the (001) surface. With half-filled flat bands apparent in the calculation, but an absence of long-range magnetic order, the unusual quasi-paramagnetic response suggests the dilute paramagnetic behavior in this quasicrystal approximant is surprising and may serve as a test of the fundamental assumptions that are taken for granted for the magnetic response of weakly interacting systems.

Avers, Keenan E. (ORCID:0000000223441939)↗

DOE OSTI2026

Hydration structure and energetics of iron-exchanged montmorillonite

The interaction between iron released from corroded steel canisters and bentonite is a key process influencing the long-term performance of nuclear waste repositories. In particular, the migration of Fe²⁺ into montmorillonite (Mnt) interlayers may alter its hydration, swelling, and ion-transport properties. In the present study, molecular dynamics simulations were performed to investigate the hydration behavior, structural response, and transport properties of Fe-exchanged montmorillonite (Fe-Mnt) under varying hydration states. The simulations focus on short- to intermediate-time-scale Fe 2+ and Fe 3+ interlayer exchange and hydration effects, and do not consider long-term structural substitution, Fe-bearing clay phase stabilization, or secondary iron mineral precipitation. Systems containing Na + -, Fe 2+ -, and Fe 3+ -Mnt were examined using both periodic and edge-exposed configurations to evaluate interlayer structure, ion exchange, and free energy of Fe intercalation. The results show that Fe ions influence the interlayer spacing primarily at low water contents (<1 bilayer), where Fe-Mnt exhibits a d-spacing 1–2 Å larger than Na-Mnt due to stronger hydration. The calculated hydration energies follow the order Fe 2+ $<$Fe 3+ $<$Na + . Both water and ion diffusion coefficients decrease upon Fe ion intercalation, with Fe 2+ ions diffusing an order of magnitude more slowly than those of Na + . Free energy profiles further confirm that Fe 2+ and Fe 3+ ions are thermodynamically favored in the interlayer, with Fe 3+ being the most stable. In conclusion, these findings provide molecular-scale insights into the mechanisms of Fe–Na exchange and their implications for bentonite alteration in repository environments.

clay↗

DOE OSTI2025

dynamics of organic-mineral interactions at the metal oxide-solution interface as studied via binding energetics (Final report)

This project focused on addressing longstanding fundamental and experimental uncertainties on how dissolved organic substances (DOS) interact with metal oxide surface under environmentally relevant conditions. By leveraging a custom-built real-time, in-tandem flow adsorption microcalorimetry-UV-Vis/fluorescence spectroscopy platform, we characterized the binding energetics, kinetics and mechanistic pathways driving DOS-metal oxide interactions at temporal resolution on the order of 1-5 seconds. We studied a diverse suite of model organic compounds/substances – including monocarboxylates (e.g. acetate and benzoate), di-carboxylates (oxalate and succinate), amino acids, amino-based nanparticles and natural organic matter – interacting at the mineral-water interface of structurally- and/or chemically distinct metal oxides (including SiO2, boehmite, ferrihydrite, and γ-Al2O3). Our results indicated that DOS-metal oxide interactions are governed by multi-step reaction pathways, often switching between distinct, resolvable enthalpy- and entropy-driven non-electrostatic or electrostatic configurations. To quantify these interactions, we developed and implemented an analytical workflow that integrates peak deconvolution and Monte-Carlo based error propagation to determine site-specific thermodynamic and kinetic parameters for individual binding/debinding events. In addition to resolving apparent first-order rate constants of each event, we were able to quantify associated apparent equilibrium constants as well as free energy, enthalpy and entropy contribution to the activation and subsequent progression of the binding/debinding process across compounds, compound class and metal oxide surfaces. The kinetic-thermodynamic data produced in this study captured how the interplay between oxide surface reactivity and DOS molecular structure jointly drives binding-debinding dynamics. Notably, that at pH below PZC of the oxide surface, neutral species were heavily involved in monocarboxylate binding, while anionic species drove dicarboxylate binding. Also, that among amino acids 1) positional isomers show distinctive binding characteristics to each other while enantiomers show no significant differences in binding characteristics, 2) molecules that bind via outer-sphere complexation show a larger entropic shift between binding and debinding with no impact on oxide surface while 3) inner-sphere interactions increased anion exchange capacity of the oxide surface. The new insights and data from this work has great potential for improving predictive modeling of carbon dynamics and specifically organic-mineral interactions in environmental and industrial systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The Role of Interfacial Interactions and Oxygen Vacancies in Tuning Magnetic Anisotropy in LaCrO 3 /LaMnO 3 Heterostructures

The interplay of lattice, electronic, and spin degrees of freedom at epitaxial complex oxide interfaces provides a route to tune their magnetic ground states. Unraveling the competing contributions is critical for tuning their functional properties. The relationship between magnetic ordering and magnetic anisotropy and the lattice symmetry, oxygen content, and film thickness in compressively strained LaMnO 3 (LMO)/LaCrO 3 (LCO) superlattices is investigated. Mn–O–Cr antiferromagnetic superexchange interactions across the heterointerface result in a net ferrimagnetic magnetic structure. Bulk magnetometry measurements reveal isotropic in-plane magnetism for as-grown oxygen-deficient thin samples due to equal fractions of orthorhombic a+a-c-, and a-a+c- twin domains. As the superlattice thickness is increased, in-plane magnetic anisotropy emerges as the fraction of the a+a-c- domain increases. On annealing in oxygen, the suppression of oxygen vacancies results in a contraction of the lattice volume, and an orthorhombic to rhombohedral transition leads to isotropic magnetism independent of the film thickness. The complex interactions are investigated using high-resolution synchrotron diffraction and X-ray absorption spectroscopy. These results highlight the role of the evolution of structural domains with film thickness, interfacial spin interactions, and oxygen-vacancy-induced structural phase transitions in tuning the magnetic properties of complex oxide heterostructures.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Single photon emitters in van der Waals solids for quantum photonics: materials, theory and molecular-scale characterization probes

Strong light–matter interactions in two-dimensional layered materials (2D materials) have attracted the interest of researchers from interdisciplinary fields for more than a decade now. A unique phenomenon in some 2D materials is their large exciton binding energies (BEs), increasing the likelihood of exciton survival at room temperature. It is this large BE that mediates the intense light–matter interactions of many of the 2D materials, particularly in their monolayer limit, where the interplay of excitonic phenomena poses a wealth of opportunities for high-performance optoelectronics and quantum photonics. Within quantum photonics, quantum information science (QIS) is growing rapidly, where photons are a promising platform for information processing due to their low-noise properties, excellent modal control, and long-distance propagation. A central element for QIS applications is a single photon emitter (SPE) source, where an ideal on-demand SPE emits exactly one photon at a time into a given spatiotemporal mode. Recently, 2D materials have shown practical appeal for QIS which is directly driven from their unique layered crystalline structure. This structural attribute of 2D materials facilitates their integration with optical elements more easily than the SPEs in conventional three-dimensional solid state materials, such as diamond and SiC. In this review article, we will discuss recent advances made with 2D materials towards their use as quantum emitters, where the SPE emission properties maybe modulated deterministically. Here, the use of unique scanning tunneling microscopy tools for the in-situ generation and characterization of defects is presented, along with theoretical first-principles frameworks and machine learning approaches to model the structure-property relationship of exciton–defect interactions within the lattice towards SPEs. Given the rapid progress made in this area, the SPEs in 2D materials are emerging as promising sources of nonclassical light emitters, well-poised to advance quantum photonics in the future.

2D layered materials↗

DOE OSTI2025

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗

DOE OSTI2026

Microbial reduction of low-crystallinity tripuhyite (FeSbO 4 ): Implications for Sb(V) cycling in contaminated environments

Tripuhyite (FeSbO 4 ) is an important antimony (Sb)-bearing mineral that controls Sb mobility in contaminated environments, yet its structural stability during microbial reduction remains unresolved. Understanding how FeSbO 4 behaves under anoxic conditions is therefore necessary to predict natural Sb cycling. Here, this study examined how an anaerobic microbial community interacts with FeSbO 4 and alters its structural and redox behavior. Across all conditions, FeSbO 4 released measurable Sb(V), demonstrating that the mineral undergoes partial dissolution in anoxic environment even without microbial activity. However, when extensive microbial Fe(III) reduction occurred in the presence of the electron shuttle anthraquinone-2,6-disulfonate (AQDS), the released Sb was re-immobilized. This indicates that microbial reduction processes modulate Sb mobility. Microbial community analysis showed the enrichment of acetate-utilizing Fe(III)-reducing bacteria as key drivers of Fe reduction. Although secondary Fe minerals were not detected, X-ray absorption fine structure measurements and scanning electron microscopy images revealed the formation of an Sb(III)-bearing phase consistent with valentinite (Sb 2 O 3 ) in the AQDS-amended treatment. This transformation suggests that AQDS not only enhances Fe(III) reduction but is also linked to Sb(V) reduction, and facilitates the immobilization of reduced Sb(III) as Sb 2 O 3 . Overall, this work provides the first evidence that FeSbO 4 is susceptible to microbially mediated redox transformations, and that these processes can significantly alter the mobility and speciation of Sb in reducing environments.

Electron transfer mediator↗

DOE OSTI2025

Unraveling the pathway towards superionic transport in polymer electrolytes

Ionic transport in polymers is critical for Li-ion batteries, fuel cells, flow batteries and many other energy storage and conversion technologies. A significant enhancement of ion conductivity in polymers may be achieved through an increase in the polarity of side chains and their self-organization into specific morphologies, which can potentially act as percolated ionic structures. However, higher polarity increases attractive interactions within a polymer matrix and slows down its segmental dynamics, which conversely hinders ionic transport. To overcome this tradeoff, we designed the functionalization of a Li salt-doped polymer matrix by tailored amounts of zwitterionic (ZI) groups. Our results suggest the emergence of a self-assembled percolation conductivity regime above a specific ZI concentration, in which ion hopping decouples from segmental dynamics by up to ten orders of magnitude. Consequently, in the highly concentrated ZI regime, our polymeric materials exhibit in their glassy state energy barriers for ion hopping similar to, or even smaller than, those reported for superionic ceramics. Our study also reveals that ion dynamics in the poly(zwitterion) with all monomers carrying ZI groups is significantly faster than that of a monomeric ZI compound, although the latter has much faster structural relaxation. Furthermore, this result highlights the crucial role played by the local morphology on the ion transport of polymer electrolytes and opens a new pathway for the design of superionic polymers, significantly expanding the current limited portfolio of solid-state electrolytes for energy applications.

Ion conductivity↗

DOE OSTI2026

Quantum Theory of Surface Lattice Resonances

The collective interactions of nanoparticles arranged in periodic structures give rise to high‐ in‐plane diffractive modes known as surface lattice resonances. Although these resonances and their broader implications have been extensively studied within the framework of classical electrodynamics and linear response theory, a quantum optical theory capable of describing the dynamics of these structures, especially in the presence of material nonlinearities beyond ad hoc few‐mode approximations, is largely missing. To this end, we consider a lattice of metallic nanoparticles coupled to the electromagnetic field and derive the quantum input–output relations within the electric dipole approximation. As applications, we analyze coupling between the nanoparticle array and external quantum emitters, and show how the formalism extends to molecular optomechanics, where the high ‐factors of SLRs enable coupling to collective vibrational modes. We further consider arrays composed of saturable excitonic emitters, demonstrating how emitter nonlinearities can be used to switch the SLR condition between electronic transitions. Using a perturbative approach that accounts for population dynamics, we show how these effects can be probed in pump–probe experiments and give rise to nonlinear phase‐matching phenomena. Our work provides a microscopic framework for modeling SLRs interacting with quantum emitters without phenomenological descriptions of the electromagnetic environment.

molecular optomechanics↗

DOE OSTI2025

Bottom-up fabrication of 2D Rydberg exciton arrays in cuprous oxide

Solid-state platforms provide exceptional opportunities for advancing on-chip quantum technologies by enhancing interaction strengths through coupling, scalability, and robustness. Cuprous oxide (Cu 2 O) has recently emerged as a promising medium for scalable quantum technology due to its high-lying Rydberg excitonic states, akin to those in hydrogen atoms. To harness these nonlinearities for quantum applications, the confinement dimensions must match the Rydberg blockade size, which can reach several microns in Cu 2 O. Using a CMOS-compatible growth technique, this study demonstrates the bottom-up fabrication of site-selective arrays of Cu 2 O microparticles. We observed Rydberg excitons up to the principal quantum number n = 5 within these Cu 2 O arrays on a quartz substrate and analyzed the spatial variation of their spectrum across the array, showing robustness and reproducibility on a large chip. These results lay the groundwork for the deterministic growth of Cu 2 O around photonic structures, enabling substantial light-matter interaction on integrated photonic platforms and paving the way for scalable, on-chip quantum devices.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Feasibility Study on Implementing a Staggered-Grid Finite Volume Method for System Analysis Code Development Under the MOOSE Framework

Here, this work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key to the test bed is the implementation of high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. The test bed utilized a more flexible code structure to enable the finite volume method implementation and direct interacting with the solver package, instead of using the natively supported finite element method by the framework. Using a suite of selected test problems with different problem sizes and levels of complexity, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. For a complex reactor model, transient simulation was performed using the newly developed finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development.

MOOSE↗

DOE OSTI2026

Actinium–DOTA coordination in water from hybrid ML/MM: Structure, free energies, and water-exchange pathways

Quantitative simulation of trivalent ƒ-block chelates in water remains challenging because bonded and non-bonded force-field models make different approximations for coordination structure, exchange dynamics, and ion–ligand interactions in highly charged systems. Here, we develop a hybrid machine-learning/molecular-mechanics (ML/MM) framework for Ac 3+ –DOTA in explicit solvent by training an E(3)-equivariant neural network potential (MACELES) on mechanically embedded QM/MM data for Ac aquo and Ac–DOTA species and coupling it to NAMD 2.14 with particle-mesh Ewald electrostatics. Nanosecond ML/MM trajectories remain numerically stable and preserve chelate integrity, yielding a compact DOTA inner shell with an inner-sphere water coordination number of CN Ac,O w ≈ 1.7 arising from a dynamic equilibrium between one- and two-water states (37.5% and 59.9% of frames; three waters 2.5%). A 5 ns potential of mean force shows two low-lying basins at CN Ac,O w ≈ 1 and CN Ac,O w ≈ 2. DFT end-state free energies are consistent with the ML/MM profile, and DFT minimum-energy paths provide a qualitative electronic-structure reference for the observed basin connectivity. State-resolved kinetics reveal picosecond water-exchange pathways that couple hydration changes to transient DOTA arm fluctuations, and training-set comparisons show that temperature-matched Ac–DOTA data optimize energy/force accuracy while more diverse solvated data improve charge prediction. Overall, the present hybrid ML/MM model provides a practical description of Ac 3+ –DOTA hydration thermodynamics and short-time exchange behavior in explicit water at MD-like cost.

Actinium↗

DOE OSTI2025

Kβ X-ray Emission Spectra Analysis Using Bayesian Optimization

The Kβ X-ray emission spectrum of 3 d transition metals is rich with electronic and structural information due to strong exchange interactions with the valence shell of the metal, and has become crucial for understanding their spin and oxidation states. The spectrum is commonly treated using crystal-field multiplet theory, a semi-empirical theory that uses tunable parameters to control the strength of the effects present in X-ray emission spectroscopy (XES). However, determining the experimental values of these parameters remains a challenge. We present a methodology that applies Bayesian optimization to crystal-field multiplet theory to determine parameter values. The algorithm is tested on the X-ray emission spectra of a collection of Mn, Co, and Ni oxides. We are able to find optimal values for the four most impactful parameters: Slater−Condon reduction factors F dd , F pd , and G pd , and crystal field splitting 10 Dq . The algorithm produces significantly improved accuracy compared to current analysis methods, and probes interparameter dependencies by modeling the error landscape. This advancement enhances XES analysis by offering an approach of obtaining quantitative electronic structural information on 3 d transition metal valence shells, facilitating applications across various scientific fields.

Bayesian optimization↗