Cure-to-service design of metastability-confined geo-stable cements
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Engineering topics
Publications and source records attributed to Ilgen, Anastasia G..
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Separating individual lanthanide (Ln) elements in aqueous mixtures is challenging. Ion-selective capture by porous materials, such as metal–organic frameworks (MOFs), is a promising approach. To design ion-selective MOFs, molecular details of the Ln adsorption complexes within the MOFs must be understood. We determine the local coordination environment of lanthanides Nd(III), Gd(III), and Lu(III) adsorbed onto Cr(III)-based terephthalate MOF (Cr-MIL-101) and Zr(IV)-based Universitet in Oslo MOFs (UiO-66 and UiO-68) and their derivatives. In the Cr(III)- and Zr(IV)-based MOFs, Ln adsorb as inner-sphere complexes at the metal oxo clusters, regardless of whether the organic linkers are decorated with amino groups. Missing linkers result in favorable Ln binding sites at oxo clusters; however, Ln can coordinate to metal sites even with linkers in place. Further, MOF functionalization with phosphonate groups led to Ln chemisorption onto these groups, which out-compete metal cluster sites. Ln form monodentate and bidentate and mononuclear and binuclear surface complexes. We conclude that MOFs for ion-selective Ln capture can be designed by a combination of (1) maximizing metal-lanthanide interactions via shared O atoms at the metal oxo cluster sites, where mixed oxo clusters can lead to ion-selective Ln adsorption, and (2) functionalizing MOFs with Ln-selective groups capable of out-completing the metal oxo cluster sites.
Solid–water interfaces are crucial for clean water, conventional and renewable energy, and effective nuclear waste management. However, reflecting the complexity of reactive interfaces in continuum-scale models is a challenge, leading to oversimplified representations that often fail to predict real-world behavior. This is because these models use fixed parameters derived by averaging across a wide physicochemical range observed at the molecular scale. Recent studies have revealed the stochastic nature of molecular-level surface sites that define a variety of reaction mechanisms, rates, and products even across a single surface. To bridge the molecular knowledge and predictive continuum-scale models, we propose to represent surface properties with probability distributions rather than with discrete constant values derived by averaging across a heterogeneous surface. This conceptual shift in continuum-scale modeling requires exponentially rising computational power. By incorporating our molecular-scale understanding of solid–water interfaces into continuum-scale models we can pave the way for next generation critical technologies and novel environmental solutions.