Prediction of apatite lattice constants from their constituent elemental radii and artificial intelligence methods

Computational Materials Design for Ceramic Nuclear Waste Forms Using Machine Learning, First-Principles Calculations, and Kinetics Rate Theory

Ceramic waste forms are designed to immobilize radionuclides for permanent disposal in geological repositories. One of the principal criteria for the effective incorporation of waste elements is their compatibility with the host material. In terms of performance under environmental conditions, the resistance of the waste forms to degradation over long periods of time is a critical concern when they are exposed to natural environments. Due to their unique crystallographic features and behavior in nature environment as exemplified by their natural analogues, ceramic waste forms are capable of incorporating problematic nuclear waste elements while showing promising chemical durability in aqueous environments. Recent studies of apatite- and hollandite-structured waste forms demonstrated an approach that can predict the compositions of ceramic waste forms and their long-term dissolution rate by a combination of computational techniques including machine learning, first-principles thermodynamics calculations, and modeling using kinetic rate equations based on critical laboratory experiments. By integrating the predictions of elemental incorporation and degradation kinetics in a holistic framework, the approach could be promising for the design of advanced ceramic waste forms with optimized incorporation capacity and environmental degradation performance. Such an approach could provide a path for accelerated ceramic waste form development and performance prediction for problematic nuclear waste elements.

Recent Advances in Corrosion Science Applicable To Disposal of High-Level Nuclear Waste

High-level radioactive waste is accumulating at temporary storage locations around the world and will eventually be placed in deep geological repositories. The waste forms and containers will be constructed from glass, crystalline ceramic, and metallic materials, which will eventually come into contact with water, considering that the period of performance required to allow sufficient decay of dangerous radionuclides is on the order of 10⁵-10⁶ years. Corrosion of the containers and waste forms in the aqueous repository environment is therefore a concern. This Review describes the recent advances of the field of materials corrosion that are relevant to fundamental materials science issues associated with the long-term performance assessment and the design of materials with improved performance, where performance is defined as resistance to aqueous corrosion. Glass, crystalline ceramics, and metals are discussed separately, and the near-field interactions of these different material classes are also briefly addressed. Finally, recommendations for future directions of study are provided.

Prediction of Lattice Constant of A2XY6 Cubic Crystals Using Gene Expression Programming

Lattice constant is one of the paramount parameters that mark the quality of thin film fabrication. Numerous research efforts have been made to calculate and measure lattice constant, including experimental and empirical approaches. Not withstanding these efforts, a reliable and simple-to-use model is still needed to predict accurately this vital parameter. In this study, gene expression programming (GEP) approach was implemented to establish trustworthy model for prediction of the lattice constant of A₂XY₆ (A = K, Cs, Rb, TI; X = tetravalent cation; and Y = F, Cl, Br, I) cubic crystals based on a comprehensive experimental database. The obtained results showed that the proposed GEP correlation provides excellent prediction performance with an overall average absolute relative deviation (AARD%) of 0.3596% and a coefficient of determination (R²) of 0.9965. Moreover, the comparison of the performance between the newly proposed correlation and the best pre-existing paradigms demonstrated that the established GEP correlation is more robust, reliable, and efficient than the prior models for prediction of lattice constant of A₂XY₆ cubic crystals.

Light Absorption Properties and Electronic Band Structures of Lead-Vanadium Oxyhalide Apatites Pb5 (VO4 )3 X (X=F, Cl, Br, I)

The Pb-V oxyhalide apatite compounds Pb₅ (VO₄ )₃ X (X=F, Cl, Br, I) were successfully synthesized using a facile solution method and studied with respect to their structural/optical characteristics and electronic band structures. UV-visible diffuse reflectance spectroscopy, electrochemical analysis and first-principles calculations showed that the synthesized apatites behaved as n-type semiconductors, with absorption bands in the UV-visible region that could be assigned to electron transitions from the valence band to a conduction band formed by hybridized V 3d and Pb 6p orbitals. Among the apatites examined, Pb₅ (VO₄ )₃ I had the smallest band gap of 2.7 eV, due to an obvious contribution of I 5p orbitals to the valence band maximum. Based on its visible light absorption capability, Pb₅ (VO₄ )₃ I generated a continuous anodic photocurrent under visible light (λ>420 nm) in a solution of 0.1 m NaI in acetonitrile.

Beta transmutations in apatites with ferric iron as an electron acceptor – implication for nuclear waste form development

The electron from beta decay is captured by the neighboring ferric ion, which is changed to the ferrous ion.

Rietveld refinement of Sr(5)(AsO(4))(3)Cl from high-resolution synchrotron data

The apatite-type compound, penta­strontium tris­[arsenate(V)] chloride, Sr₅(AsO₄)₃Cl, has been synthesized by ion exchange at high temperature from a synthetic sample of mimetite [Pb₅(AsO₄)₃Cl] with SrCO₃ as a by-product. The results of the Rietveld refinement, based on high resolution synchrotron X-ray powder diffraction data, show that the title compound crystallizes in the same structure as other halogenoapatites with general formula A₅(YO₄)₃X (A = divalent cation, Y = penta­valent cation, and X = F, Cl or Br) in the space group P6₃/m. The structure consists of isolated tetra­hedral AsO₄³⁻ anions (the As atom and two O atoms have m symmetry), separated by two crystallographically independent Sr²⁺ cations that are located on mirror planes and threefold rotation axes, respectively. One Sr atom is coordinated by nine O atoms and the other by six. The chloride anions (site symmetry ) are at the 2a sites and are located in the channels of the structure.

Rietveld refinement of Ba(5)(AsO(4))(3)Cl from high-resolution synchrotron data

The apatite-type compound Ba₅(AsO₄)₃Cl, penta­barium tris­[arsenate(V)] chloride, has been synthesized by ion exchange at high temperature from a synthetic sample of mimetite (Pb₅(AsO₄)₃Cl) with BaCO₃ as a by-product. The results of the Rietveld refinement, based on high resolution synchrotron X-ray powder diffraction data, show that the title compound crystallizes in the same structure as other halogenoapatites with general formula A₅(YO₄)₃X (A = divalent cation, Y = penta­valent cation, X = Cl, Br) in space group P6₃/m. The structure consists of isolated tetra­hedral AsO₄³⁻ anions (m symmetry), separated by two crystallographically independent Ba²⁺ cations that are located on mirror planes and threefold rotation axes, respectively. The Cl⁻ anions are at the 2b sites ( symmetry) and are located in the channels of the structure.

Predicting the efficiency of UAG translational stop signal through studies of physicochemical properties of its composite mono- and dinucleotides

In this study, we explored the problem of predicting the UAG stop-codon read-through efficiency. The reported nucleotide sequences were first converted into physicochemical property vectors before being presented to a machine learning algorithm. Two sets of physicochemical properties were applied: one for mononucleosides (in terms of steric bulk, hydrophobicity and electronics) and another for dinucleotides. To the best of our knowledge, this is the first report of how dinucleotides are converted into principle components derived from NMR chemical shift data. A few efficiency prediction models were then derived and a comparison between mononucleoside and dinucleotide-based models was shown. In the derived models, the coefficients of these property based predictors lend themselves to bio-physical interpretations, an advantage which is demonstrated in this study via a prediction model based on the steric bulk factor. Although it is quite simple, the steric bulk factor model explained well the effect of sequence variations surrounding the amber stop codon and the tRNA bearing UCCU anticodon. We further proposed new alternatives at position -1 and +4 of a UAG stop codon sequence to enhance the readthrough efficiency. This research may contribute to a better understanding of the readthrough mechanisms and may also help to study the normal translation termination process.