Density functional modeling of the binding energies between aluminosilicate oligomers and different metal cations

Interactions between negatively charged aluminosilicate species and positively charged metal cations are critical to many important engineering processes and applications, including sustainable cements and aluminosilicate glasses. In an effort to probe these interactions, here we have calculated the pair-wise interaction energies (i.e., binding energies) between aluminosilicate dimer/trimer and 17 different metal cations Mn+ (Mn+ = Li+, Na+, K+, Cu+, Cu2+, Co2+, Zn2+, Ni2+, Mg2+, Ca2+, Ti2+, Fe2+, Fe3+, Co3+, Cr3+, Ti4+ and Cr6+) using a density functional theory (DFT) approach. Analysis of the DFT-optimized structural representations for the clusters (dimer/trimer + Mn+) shows that their structural attributes (e.g., interatomic distances) are generally consistent with literature observations on aluminosilicate glasses. The DFT-derived binding energies are seen to vary considerably depending on the type of cations (i.e., charge and ionic radii) and aluminosilicate species (i.e., dimer or trimer). A survey of the literature reveals that the difference in the calculated binding energies between different Mn+ can be used to explain many literature observations associated with the impact of metal cations on materials properties (e.g., glass corrosion, mineral dissolution, and ionic transport). Analysis of all the DFT-derived binding energies reveals that the correlation between these energy values and the ionic potential and field strength of the metal cations are well captured by 2nd order polynomial functions (R2 values of 0.99–1.00 are achieved for regressions). Given that the ionic potential and field strength of a given metal cation can be readily estimated using well-tabulated ionic radii available in the literature, these simple polynomial functions would enable rapid estimation of the binding energies of a much wider range of cations with the aluminosilicate dimer/trimer, providing guidance on the design and optimization of sustainable cements and aluminosilicate glasses and their associated applications. Finally, the limitations associated with using these simple model systems to model complex interactions are also discussed

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences

GEL AND PORE STRUCTURE FORMATION IN ALKALI-ACTIVATED MATERIALS

As the cement industry accounts for 5 – 8 % of global anthropogenic CO2 emissions, there is an urgent need to curtail the greenhouse gas emission from the cement industry. The adoption of alternative binding materials, such as alkali-activated materials (AAMs), in place of traditional ordinary Portland cement (OPC) can not only reduce the CO2 emission, but also provide other benefits such as waste valorization. However, our knowledge on the long-term performance of AAMs is considerably limited as there are few in-field applications for service life evaluation. This thesis aims to take on the challenge of resolving the durability of AAMs, which is arguably the most critical roadblock for their commercial scale adoption. Concretely, this thesis centers on the development of a generic computational paradigm, that is, a density functional theory-based coarse-grained Monte Carlo (DFT-CGMC) approach, with the ultimate goal to predict transport properties of AAMs and related materials. This thesis is organized according to the general workflow of the DFT-CGMC approach. Chapter 4 is devoted to modeling of the Gibbs free energy of pair-wise interaction between dissolved molecular species prevalent in AAM and OPC systems via DFT calculation, where the early stage formation mechanisms of calcium-silicate-hydrate (C-S-H) and sodium-based calcium aluminosilicate hydrate (C-(N)-A-S-H) gels, the major binding phase of OPC and AAM, respectively, are proposed. Chapter 5 focuses on augmenting the capability of the DFT-CGMC approach via incorporating calcium species into the model, which is validated by simulating solubility of Ca(OH)2 and comparing the result against experimental data. Chapter 6 centers on a low-calcium variant of AAMs, that is, alkali-activated metakaolin (AAMK). Concretely, the simulated pore structure of AAMK is extracted and compared against pore size distribution data from nitrogen sorption experiment, where semi-quantitative agreement is found. Besides, the pore size distributions of AAMK with different silicon concentrations across length scales are revealed. Lastly, Chapter 7 is an experimental study on the atomic changes of C-(N)-A-S-H gel (from silicate-activated slag) subjected to drying condition via X-ray pair distribution function analysis, serving as a case study showcasing the importance of the knowledge of transport properties of AAMs and related materials

DataSheet1_Density functional modeling of the binding energies between aluminosilicate oligomers and different metal cations.pdf

Interactions between negatively charged aluminosilicate species and positively charged metal cations are critical to many important engineering processes and applications, including sustainable cements and aluminosilicate glasses. In an effort to probe these interactions, here we have calculated the pair-wise interaction energies (i.e., binding energies) between aluminosilicate dimer/trimer and 17 different metal cations Mn+ (Mn+ = Li+, Na+, K+, Cu+, Cu2+, Co2+, Zn2+, Ni2+, Mg2+, Ca2+, Ti2+, Fe2+, Fe3+, Co3+, Cr3+, Ti4+ and Cr6+) using a density functional theory (DFT) approach. Analysis of the DFT-optimized structural representations for the clusters (dimer/trimer + Mn+) shows that their structural attributes (e.g., interatomic distances) are generally consistent with literature observations on aluminosilicate glasses. The DFT-derived binding energies are seen to vary considerably depending on the type of cations (i.e., charge and ionic radii) and aluminosilicate species (i.e., dimer or trimer). A survey of the literature reveals that the difference in the calculated binding energies between different Mn+ can be used to explain many literature observations associated with the impact of metal cations on materials properties (e.g., glass corrosion, mineral dissolution, and ionic transport). Analysis of all the DFT-derived binding energies reveals that the correlation between these energy values and the ionic potential and field strength of the metal cations are well captured by 2nd order polynomial functions (R2 values of 0.99–1.00 are achieved for regressions). Given that the ionic potential and field strength of a given metal cation can be readily estimated using well-tabulated ionic radii available in the literature, these simple polynomial functions would enable rapid estimation of the binding energies of a much wider range of cations with the aluminosilicate dimer/trimer, providing guidance on the design and optimization of sustainable cements and aluminosilicate glasses and their associated applications. Finally, the limitations associated with using these simple model systems to model complex interactions are also discussed.</p

Anisotropic crystallization in solution processed chalcogenide thin film by linearly polarized laser

The low activation energy associated with amorphous chalcogenide structures offers broad tunability of material properties with laser-based or thermal processing. In this paper, we study near-bandgap laser induced anisotropic crystallization in solution processed arsenic sulfide. The modified electronic bandtail states associated with laser irritation lead to a distinctive photoluminescence spectrum, compared to thermally annealed amorphous glass. Laser crystalized materials exhibit a periodic subwavelength ripples structure in transmission electron microscopy experiments and show polarization dependent photoluminescence. Analysis of the local atomic structure of these materials using laboratory-based X-ray pair distribution function analysis indicates that laser irradiation causes a slight rearrangement at the atomic length scale, with a small percentage of S-S homopolar bonds converting to As-S heteropolar bonds. These results highlight fundamental differences between laser and thermal processing in this important class of materials

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences