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At least 811 records · Page 45

A physics informed model for the prediction of surface energies and the shape of metal particles

Surface energies of metal-based systems are important for determining the Wulff-constructed shapes of metal nanoparticles and understanding the stability. We have developed a physics informed method to predict the total energy of metal-based systems across a wide range of configurations. Our method has been tested against density functional theory (DFT) calculations for late transition metals. This method enables on-the-fly surface energy predictions based on the fundamental of materials property and allows for the Wulff construction of metal particles for a random number of elemental atoms and without the need for DFT calculations. By making a division between atoms in the different layers of the model system, we can improve the accuracy of the model, suggesting a dissimilarity between the electronic structure due to an alternating compression and expansion of atomic layers. We find that our model accurately and effectively provides valuable insights into the distribution and stability of nanoparticles.

Mandal, Shyama Charan (ORCID:0000000245882874)↗

Investigating the non-classical M-H 2 bonding in OsClH 3 (PPh 3 ) 3

Dihydrogen ligation to metal centers results in a wide range of metal-hydrogen interactions. Compounds containing non-classical dihydrogen ligands in which the H-H contacts are significantly longer than the 0.74 A distance found in solid H 2 are classified as Kubas-like compounds, stretched dihydrogen ligands, or compressed dihydrides, depending on the H-H contact length. Compounds containing stretched dihydrogen and compressed dihydride ligands are somewhat rare. Developing a more complete understanding of the metal-hydrogen and hydrogen-hydrogen interactions in these species may provide insights into the mechanisms for the oxidative addition reaction and hydrogen storage. Here, we use diffraction and inelastic neutron scattering (INS) measurements, paired with both molecular and solid-state density functional theory (DFT), to fully characterize the nature of the metal-hydrogen and hydrogen-hydrogen interactions in a previously reported compound, OsClH 3 (PPh 3 ) 3 . In that report, the H-H distance was measured as 1.48(2) A by single-crystal neutron diffraction and was described as a "stretched" dihydrogen. The INS-generated phonon density of states is well described by the DFT calculations, including those normal modes dominated by the vibrational motions of the three Os-ligated hydrogen atoms. Additionally, the resulting calculated electron charge density landscape indicates that there is no remnant bonding character between the Os-ligated hydrogen atoms in the compound. Based on these findings, we update the understanding of the metal-hydrogen bonding in this complex and reclassify it as a compressed dihydride. As such, OsClH 3 (PPh 3 ) 3 represents a rare example of a non-classical compressed dihydride species.

08 HYDROGEN↗

Be₂C as a neutron moderator for molten salt reactors: A first-principles study of structural, electronic, and defect properties

Beryllium carbide (Be 2 C), valued for its high neutron moderation efficiency and low absorption cross section, is a promising high-temperature neutron moderator for molten salt reactors. Its practical adoption, however, demands significant technological maturation, requiring comprehensive theoretical and experimental studies of its response to different conditions, including high temperature and irradiation. Here, we report initial results on the fundamental properties and radiation-induced defects of Be 2 C, focusing on antisites, vacancies, interstitial atoms, and Frenkel pairs in the Be and C sublattices. Using density functional theory (DFT) and ab initio molecular dynamics (AIMD), we calculate the defects formation and binding energies, evaluating their dependence on the supercell size, charge states, and chemical environment. In general, carbon defects exhibit higher formation energies, greater sensitivity to cell size, and stronger impacts on the density of states compared to beryllium defects, with charged state the effects being more pronounced. Static DFT reveals multiple metastable interstitial configurations, while AIMD identifies ground states as C-C <100> dumbbells and octahedral Be interstitials. In conclusion, the diversity of metastable configurations and defect states complicates the diffusion mechanisms, requiring further molecular dynamics analysis to elucidate the mechanisms and rates of radiation-induced atomic transport, as well as the structural stability of Be2C.

Ab initio modeling↗

The presence of Ru metal modifies the behavior of deuterium bound to pyridinic nitrogen in doped graphene-like materials

We used a combination of x-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) to investigate how the presence of a ruthenium (Ru) metal substrate modifies the N-D bond strength of the pyridinic nitrogen species in nitrogen (N)-doped graphene (Gr) on Ru(0001) compared to metal-free highly-oriented pyrolytic graphite (HOPG) substrate. The N-dopants were introduced through low-energy N+/N2+ irradiation. N is embedded in the carbon materials in two predominant configurations: as graphitic N (GN: N substituted in the hexagonal C lattice) and pyridinic N (PN: substitutional N adjacent to a C vacancy). XPS data showed that upon atomic deuterium (D) exposure at 220 K, the PN peak shifted to a higher binding energy by +1.2 eV for HOPG and +1.0 eV for N-doped graphene on Ru(0001), while the GN peak remained unchanged, indicating that the D atoms bound solely to pyridinic N. 85% of PN sites on HOPG can be saturated with D atoms, whereas only ~30% of pyridinic N sites are able to bind D atoms in N-doped Gr/Ru(0001). Our DFT analysis shows that this difference is due to the coordination of PN to Ru atoms, which necessitates bond cleavage of the N-Ru interaction prior to D atom adsorption. D begins desorbing from N-HOPG at ~573 K and is fully desorbed by ~973 K, whereas desorption from N-doped graphene on Ru(0001) begins at ~290 K, with complete desorption observed at ~700 K, indicating that the Ru metal weakens the N-D bond strength. We also studied a high-surface-area, layered, and porous N-doped carbon material, internally labeled NC900, which was synthesized by pyrolysis of glucose and graphitic carbon nitride (g-C3N4) at 1173 K. D exposure caused a +1.1 eV PN peak shift in NC900, with no change in the GN peak. Moreover, the NC900 exhibited the same desorption behavior as HOPG, demonstrating that well-defined model systems can effectively capture the behavior of more complex N-doped carbon materials.

Alupothe Gedara, Buddhika S.↗

Structure of 3-mercaptopropionic acid dioxygenase with a substrate analog reveals bidentate substrate binding at the iron center

Thiol dioxygenases are a subset of nonheme iron oxygenases that catalyze the formation of sulfinic acids from sulfhydryl-containing substrates and dioxygen. Among this class, cysteine dioxygenases (CDOs) and 3-mercaptopropionic acid dioxygenases (3MDOs) are the best characterized, and the mode of substrate binding for CDOs is well understood. However, the manner in which 3-mercaptopropionic acid (3MPA) coordinates to the nonheme iron site in 3MDO remains a matter of debate. A model for bidentate 3MPA coordination at the 3MDO Fe-site has been proposed on the basis of computational docking, whereas steady-state kinetics and EPR spectroscopic measurements suggest a thiolate-only coordination of the substrate. To address this gap in knowledge, we determined the structure of Azobacter vinelandii 3MDO (Av3MDO) in complex with the substrate analog and competitive inhibitor, 3-hydroxypropionic acid (3HPA). The structure together with DFT computational modeling demonstrates that 3HPA and 3MPA associate with iron as chelate complexes with the substrate-carboxylate group forming an additional interaction with Arg168 and the thiol bound at the same position as in CDO. A chloride ligand was bound to iron in the coordination site assigned as the O 2 -binding site. Supporting HYSCORE spectroscopic experiments were performed on the (3MPA/NO)-bound Av3MDO iron nitrosyl (S = 3/2) site. In combination with spectroscopic simulations and optimized DFT models, this work provides an experimentally verified model of the Av3MDO enzyme–substrate complex, effectively resolving a debate in the literature regarding the preferred substrate-binding denticity. These results elegantly explain the observed 3MDO substrate specificity, but leave unanswered questions regarding the mechanism of substrate-gated reactivity with dioxygen.

36 MATERIALS SCIENCE↗

Kinetics of low-temperature methane activation on IrO 2 (1 1 0): Role of local surface hydroxide species

The ability of the IrO 2 (1 1 0) surface to promote CH 4 activation at low temperatures (~150 K) suggests possibilities for developing IrO 2 -based catalysts to selectively convert light alkanes to high-value chemicals. In this study, we present experimental results and microkinetic simulations, based on density functional theory (DFT) calculations, of temperature programmed reaction spectra (TPRS) obtained for CH 4 σ-complexes adsorbed on IrO 2 (1 1 0), and focus on clarifying how surface OH groups modify the branching between CH 4 desorption, activation and subsequent reactions during TPRS. Our DFT results predict that surface OH groups strongly destabilize CH 4 σ-complexes on IrO 2 (1 1 0) in addition to deactivating surface O-atoms that are needed to achieve CH 4 activation at low temperature. We demonstrate that a microkinetic model that incorporates the influence of surface OH groups on the CH 4 binding and reactivity reproduces experimental TPRS results which show that adsorbed CH 4 σ-complexes preferentially dissociate at low CH 4 coverage, but that an increasing fraction of the adsorbed CH 4 desorbs at low temperature (~120 K) with increasing initial CH 4 or H coverage. The simulations reveal that low-temperature CH4 desorption during TPRS arises primarily from CH 4 σ-complexes that are kinetically-trapped between adjacent surface OH groups, and are thus destabilized and unable to access reactive O-atoms. In addition, when the effect of adjacent OH groups is incorporated we find that the PBE-D3 functional incorporating dispersion provides CH 4 binding energies that agree more closely with that obtained from the TPRS experiments. Overall, our results demonstrate that the local effect of adjacent OH groups must be incorporated into any microkinetic models to properly capture the selectivity between extensive and partial oxidation in alkane conversion on IrO 2 (1 1 0) under reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the influence of solvents on the Pt-catalyzed hydrodeoxygenation of guaiacol

Bio-oil derived from fast pyrolysis of lignocellulosic biomass needs to be deoxygenated to become a substitute for petroleum fuels. Here, we study the hydrodeoxygenation mechanism of guaiacol, a bio-oil model compound derived from the lignin fraction of biomass, on Pt(1 1 1) terrace sites in the presence of water, diethyl ether, 1-butanol, and n-hexane as solvent. Using first-principles periodic density functional theory (DFT) calculations and mean-field microkinetic reactor modeling, a detailed reaction mechanism is investigated targeting various products such as catechol, phenol, anisole, benzene, cyclohexanone, and cyclohexanol. Solvent phase DFT outcomes are mostly similar to that of the vapor phase; however, microkinetic modeling results suggest that rate controlling species and transition states differ somewhat in the various reaction environments. Catechol was found to be the major aromatic product across all reaction environments. Over Pt(1 1 1), unsaturated monooxygenate production from catechol is unlikely.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic and kinetic relevance of hydrogen and water in CO 2 hydrogenation on Cu-based catalysts

Here, we ally steady-state kinetics, kinetic isotope effects, and density functional theory (DFT) calculations to illustrate that Cu-based catalysts remain saturated by H-adatoms (H*) and molecular formic acid (HCOOH**) during CO 2 hydrogenation. High H* coverage under methanol synthesis conditions is evidenced by reverse water-gas shift (RWGS) rates that exhibit positive H 2 reaction orders only at P H2 ≲ 0.5 bar, above which methanol synthesis and RWGS rates exhibit first and zeroth order dependence on P H2 , respectively. HCOOH** also accumulates on the surface with increasing P CO2 as informed by the Langmuir-type dependence on P CO2 (0.25-23 bar) for both methanol synthesis and RWGS. As both HCOOH** and H* have one H-atom per site occupied, the two species share the same P H2 dependence and give rise to CO 2 reaction orders that are independent of P H2 . Surface coverages determined based on kinetic analyses are further corroborated with DFT-derived adsorption energies that show favorable HCOOH** adsorbate-adsorbate interactions as well as repulsive interactions for bidentate formate (HCOO**) on H*-saturated surfaces. Methanol selectivity remains invariant with P CO2 and P CO despite CO inhibiting reaction rates, thereby demonstrating methanol synthesis and RWGS occur on the same active site. In contrast, water preferentially inhibits methanol synthesis rates, increases methanol synthesis H 2 reaction order from 1.0 to 1.5, and alters the methanol synthesis H 2 /D 2 kinetic isotope effect; the inhibitory effect of H 2 O thus cannot be attributed to competitive adsorption alone and instead reflects a change in the rate-determining step for methanol synthesis. The disparate kinetics of methanol synthesis and RWGS evince a branching pathway where methanol is formed from formates and CO is formed from carboxylates. The presented work thus identifies the relevant surface species, underscores the distinct catalytic role of water in branching methanol synthesis and RWGS pathways, and, in doing so, details a mechanistic picture that yields predictable rates and reaction orders for both methanol synthesis and RWGS on Cu-based CO 2 hydrogenation catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Proper orthogonal descriptors for efficient and accurate interatomic potentials

Here, we present the proper orthogonal descriptors for efficient and accuracy representation of the potential energy surface. The potential energy surface is represented as a many-body expansion of parametrized potentials in which the potentials are functions of atom positions and parameters. The proper orthogonal decomposition is employed to decompose the parametrized potentials into a set of proper orthogonal descriptors (PODs). Because of the rapid convergence of the proper orthogonal decomposition, relevant snapshots can be sampled exhaustively to represent the atomic neighborhood environment accurately with a small number of descriptors. The proper orthogonal descriptors are used to develop interatomic potentials by using a linear expansion of the descriptors and determining the expansion coefficients from a weighted least-squares regression against a density functional theory (DFT) training set. We present a comprehensive evaluation of the POD potentials on previously published DFT data sets comprising Li, Mo, Cu, Ni, Si, Ge, and Ta elements. The data sets represent a diverse pool of metals, transition metals, and semiconductors. The accuracy of the POD potentials are comparable to that of state-of-the-art machine learning potentials such as the spectral neighbor analysis potential (SNAP) and the atomic cluster expansion (ACE).

97 MATHEMATICS AND COMPUTING↗

Unconventional pressure-induced magnetic transitions and mechanical properties in non-magnetic LaFeSi

Here, this work demonstrates that two consecutive magnetic transitions occur in non-magnetic LaFeSi compound under negative hydrostatic pressure (small volume expansion). Electronic structure properties of LaFeSi were calculated using density functional theory (DFT) to understand the origin of these magnetic transitions. Mechanical properties of LaFeSi, especially elastic properties (shear and Young’s modulus, and Poisson’s ratio), were determined by DFT distortion calculations to elucidate lattice anisotropy and stability. The antiferromagnetic transition at –7.52 GPa, predicted in our work for LaFeSi, is consistent with the reported experimentally observed antiferromagnetic ground states in CeMnSi and LaMnSi compounds having similar crystal geometry. This finding of unexpected magnetic ordering predicts that layered non-magnetic materials, like LaFeSi, may become magnetically active with lattice expansion.

36 MATERIALS SCIENCE↗

Effects of Sn addition on precipitation of Al–Zn–Mg alloy at early stage of natural aging

The effect of Sn addition on the natural aging behavior of Al–Zn–Mg alloy was investigated using atom probe tomography (APT) experiments and density functional theory (DFT) calculations. The results demonstrate that Sn retards the natural aging behavior by facilitating the preferential formation of Mg–Sn clusters, which suppress the formation of Guinier-Preston zones (I) during the earliest aging stage. Quantitative solute analysis conducted by APT has suggested increasing amount of Mg–Sn clusters in Sn-contained alloy due to their high binding energy, supported by DFT calculations on the Sn.

36 MATERIALS SCIENCE↗

Bulk and surface diffusion of neodymium in alpha-uranium: Ab initio calculations and kinetic Monte Carlo simulations

A fundamental understanding of lanthanide transport in metallic fuels is critical for high fidelity modeling of the fuel-cladding chemical interaction (FCCI) phenomenon, which can lead to the formation of brittle intermetallic compounds and premature failure of the cladding. Here we report a combined ab initio density functional theory (DFT) and kinetic Monte Carlo (KMC) study of the bulk diffusivity of Nd in α-U, fully taking into account the effect of radiation enhanced diffusion. In this work, the vacancy mechanism is considered to be the dominant mechanism for the bulk diffusion of Nd since a Nd interstitial is found to be intrinsically unstable in α-U. The surface diffusivity of a Nd adatom on α-U (001) surface has been further predicted using KMC simulations parameterized by DFT calculations. The present study suggests that Nd transport via the surface diffusion mechanism can be many orders of magnitude faster than bulk diffusion. Furthermore, the results from the present lower length scale study can be used to inform mesoscale phase-field simulations to determine the effective diffusion coefficient of Nd through α-U with a porous microstructure.

36 MATERIALS SCIENCE↗

Atomistic and cluster dynamics modeling of fission gas (Xe) diffusivity in TRISO fuel kernels

TRISO fuel particles are candidates for use in next generation reactors including gas reactors, fluoride salt-cooled high temperature reactors, and micro-reactors. The UCO fuel kernel consists of a uranium dioxide (UO) and uranium carbide mixture. The addition of UC helps suppress the formation of carbon monoxide gas, which led to failures during initial TRISO development. The addition of uranium carbide alters the chemistry of the UO kernel, which is known to influence performance parameters such as fission gas diffusivity, although the impact has not been quantified and no models exist that take the change in chemistry into account. Therefore, better understanding and more accurate models of the impact of chemistry on fuel performance are of high priority. In this paper, a first-principles density functional theory (DFT) and empirical potential based multi-scale study has been carried out to model the diffusivity of fission gas xenon (Xe) in UCO TRISO fuel kernels. The focus is on the UO component in the UCO fuel kernels, as that represents the largest volume fraction of the fuel kernels. The study relies on DFT and empirical potential calculations to determine Xe and point defect properties, which are then used in thermodynamic and kinetic models to predict diffusion for intrinsic conditions. In addition, the information is utilized in cluster dynamics simulations using the Centipede code to estimate the impact of irradiation on defect transport. Additionally, the presence of UC or UC in the UCO fuel kernels is shown to have a substantial impact on the UO non-stoichiometry by inducing oxygen vacancies and driving UO sub-stoichiometric, which causes much slower Xe diffusion in UCO compared to light water reactor UO fuel. The application of this model in fuel performance simulations using the Bison code is also demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hydrogen trapping energetics at BCC iron-helium interfaces

Density functional theory (DFT) calculations have been performed to assess the trapping and segregation strength of hydrogen (H) to helium (He) interfaces in BCC (Fe) as a function of He density and surface orientation. The He density ranges from 0 to 2 He/V which corresponds to equilibrium bubbles that are expected to form in the structural components in a fusion reactor environment. The DFT calculations consist of a slab of BCC metal and an initial lattice of FCC He. Here, the report on the binding energy of H to these interfaces as well as the migration barriers into and away from the surface, which together provide information on the de-trapping energy for H at He bubbles. It was found that the binding energy of H to He-Fe interfaces decreases with increasing He density. Migration barriers are also modified due to the He density, which are sensitive to the surface orientation as well as the diffusion pathway. These results provide valuable first-principles energetics that are necessary for higher-order, mesoscale models, and provide insight into the extent to which He bubbles may trap tritium in fusion structural materials.

42 ENGINEERING↗

Computational insights into the lattice dynamics of Pu(IV) oxalates

Despite its use in PuO 2 production, the structure of anhydrous Pu(C 2 O 4 ) 2 is still not completely understood. Recently, two candidate structures for Pu(C 2 O 4 ) 2 were proposed via density functional theory (DFT), after which the first experimental optical vibrational spectra were reported. Here, in this study, we calculated the lattice dynamics of the candidate structures using DFT and found that the primary difference between them is the presence of a vibrational mode near 1380 cm -1 in one structure. The frequency and optical activity of this mode agree well with the published experimental results, providing strong support for this calculated structure as that of anhydrous Pu(C 2 O 4 ) 2 .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Accurate Fe–He machine learning potential for studying He effects in BCC-Fe

Nanostructured Ferritic Alloys (NFAs) containing oxide nanoparticles are prospective advanced structural materials in future fusion reactors. Lacking fusion neutron sources with an adequate flux, modeling is critical to understand radiation damage in the NFAs, including helium effects. Machine learning interatomic potentials (MLPs) have been demonstrated to be capable of describing atomic interactions in chemically complex systems with comparable accuracy to density functional theory (DFT) but with much less computational costs. Hence, MLPs are chosen to study He bubble accumulation in chemically complex NFAs. As a preliminary step, we develop a Fe–He potential, based on ~10,000 atomic configurations. The developed MLP accurately predicts the bulk properties of BCC-Fe compared to DFT, including the lattice constant (2.832 Å), elastic constants (c 11 = 271 GPa, c 12 = 141, c 44 = 93), and phonon frequencies (maximum error < 3.5%). The MLP predicts He binding energies in He n V bubbles and He n clusters with a mean absolute error (MAE) of only ~70 meV, which is ~3 to ~5 times smaller than the MAE of binding energies estimated using empirical potentials. The MLP also accurately predicts the migration barrier of interstitial He (64 meV). Furthermore, the MLP correctly predicts the maximum number of He atoms (critical size) at which a He n V bubble (He n cluster) can kick-out a self-interstitial atom (SIA), forming a bigger He n V 2 bubble (He n V bubble). Subsequently, we use the MLP to perform molecular dynamics simulations to investigate the effect of temperature on the critical size of He n V bubbles and He n clusters. We find that the critical size decreases with increasing temperature — indicating that smaller bubbles and clusters can kick-out an SIA at higher temperatures, thereby escalating the He bubble growth. We report the current Fe–He MLP can be further developed to include all chemical interactions in NFAs.

36 MATERIALS SCIENCE↗

KCl-UCl 3 molten salts investigated by Ab Initio Molecular Dynamics (AIMD) simulations

Ab Initio Molecular Dynamics (AIMD) simulations are performed on molten KCl-UCl3 salt mixtures to determine energies, heat capacities, and densities. The density-dependent energy correction (DFT-dDsC), Grimme et al.'s DFT-D3, and Langreth & Lundqvist (vdW-cx) models are used for dispersion forces and combined with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential with a Hubbard U parameter for the 5f electrons of uranium. After validating predictions for the end-member systems to literature data, KCl-UCl 3 mixtures are studied at select temperatures. Densities and energies both deviate from ideal solution behavior, with the maximum deviation occurring around 36% UCl 3 for mixing energies and slightly lower (29% UCl3) for densities. Compared to the NaCl-UCl 3 system, which was previously investigated using the same simulation methodologies, the KCl-UCl 3 density and mixing energy deviations from ideal solution behavior are larger by almost a factor of two. No deviation from ideal solution behavior for heat capacity was observed. The AIMD predictions for mixing energies and densities agree qualitatively with experimental data, though the spread in data obtained from the various dispersion force models utilized, measurements, and empirical estimates makes strong conclusions difficult. The dependence of thermodynamic and thermophysical properties on composition is correlated with the local chemistry of the solution phase, in particular, the tendency of UCl 3 to form network structures.

36 MATERIALS SCIENCE↗

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.↗